Eye-Tracking Processes and Styles in Sight Translation [1st ed.] 9789811556746, 9789811556753

Table of contents :
Front Matter ....Pages i-xxi
Introduction (Wenchao Su)....Pages 1-7
Issues and Approaches to CTIS (Wenchao Su)....Pages 9-18
Translation Style in Sight Translation (Wenchao Su)....Pages 19-47
Eye-Tracking Method (Wenchao Su)....Pages 49-68
Global and Local Styles of Sight Translation (Wenchao Su)....Pages 69-126
Gaze Behaviors, Interpreting Styles, and Language Specificity (Wenchao Su)....Pages 127-149
Looking Ahead (Wenchao Su)....Pages 151-155
Back Matter ....Pages 157-158

Citation preview

New Frontiers in Translation Studies

Wenchao Su

Eye-Tracking Processes and Styles in Sight Translation

New Frontiers in Translation Studies Series Editor Defeng Li Center for Studies of Translation, Interpreting and Cognition University of Macau, Macao SAR, China

Translation Studies as a discipline has witnessed the fastest growth in the last 40 years. With translation becoming increasingly more important in today’s glocalized world, some have even observed a general translational turn in humanities in recent years. The New Frontiers in Translation Studies aims to capture the newest developments in translation studies, with a focus on: • Translation Studies research methodology, an area of growing interest amongst translation students and teachers; • Data-based empirical translation studies, a strong point of growth for the discipline because of the scientific nature of the quantitative and/or qualitative methods adopted in the investigations; and • Asian translation thoughts and theories, to complement the current Eurocentric translation studies. Submission and Peer Review: The editor welcomes book proposals from experienced scholars as well as young aspiring researchers. Please send a short description of 500 words to the editor Prof. Defeng Li at Springernfi[email protected] and Springer Senior Publishing Editor Rebecca Zhu: [email protected]. All proposals will undergo peer review to permit an initial evaluation. If accepted, the final manuscript will be peer reviewed internally by the series editor as well as externally (single blind) by Springer ahead of acceptance and publication.

More information about this series at http://www.springer.com/series/11894

Wenchao Su

Eye-Tracking Processes and Styles in Sight Translation

123

Wenchao Su Guangdong University of Foreign Studies Guangzhou, China

ISSN 2197-8689 ISSN 2197-8697 (electronic) New Frontiers in Translation Studies ISBN 978-981-15-5674-6 ISBN 978-981-15-5675-3 (eBook) https://doi.org/10.1007/978-981-15-5675-3 © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2020 This work is subject to copyright. All rights are solely and exclusively licensed by the Publisher, whether the whole or part of the material is concerned, specifically the rights of translation, reprinting, reuse of illustrations, recitation, broadcasting, reproduction on microfilms or in any other physical way, and transmission or information storage and retrieval, electronic adaptation, computer software, or by similar or dissimilar methodology now known or hereafter developed. The use of general descriptive names, registered names, trademarks, service marks, etc. in this publication does not imply, even in the absence of a specific statement, that such names are exempt from the relevant protective laws and regulations and therefore free for general use. The publisher, the authors and the editors are safe to assume that the advice and information in this book are believed to be true and accurate at the date of publication. Neither the publisher nor the authors or the editors give a warranty, expressed or implied, with respect to the material contained herein or for any errors or omissions that may have been made. The publisher remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. This Springer imprint is published by the registered company Springer Nature Singapore Pte Ltd. The registered company address is: 152 Beach Road, #21-01/04 Gateway East, Singapore 189721, Singapore

To my mother, 胡晶

Acknowledgements

This book is largely based on my Ph.D. thesis completed at Centre for Studies of Translation, Interpreting and Cognition (CSTIC), University of Macau. I would like to express my deepest gratitude to my supervisor, Prof. Defeng Li, for his thoughtfulness, patience, and guidance over the years of my Ph.D. program. He introduced me to the world of data-based empirical studies and the application of eye-tracking technology to the research on translators’ behaviors and the cognitive processes of translation and interpreting. My special thanks go to Prof. Frans De Laet for his careful reading of my thesis, generous sharing of his tremendous knowledge about sight translation, and the promptest provision of his valuable comments on my research. I am also grateful to Prof. Arnt Lykke Jakobsen for answering my questions and offering me his insights on translation and interpreting cognition. I’m also indebted to Profs. Daniel Gile, Adolfo M. García, Laura Winther Balling, Erik Angelone, Moritz Schaeffer, Vincent Xian Wang, Matthew Wallace, Ming Yan, and Jukka Hyönä for their academic guidance. Thanks are also given to Dr. Chun Kau Chu and Dr. Arndt Heilmann for teaching me R programming. I also want to thank all the interpreters who have volunteered their time for the experiments conducted in preparation for the book. I also want to thank my friends, Ms. Apricot Zhao and Miss Nan Zhang, for their friendship and company. I am extremely grateful to my parents, Jing and Guoqiang, for their love and encouragement. I am grateful to my husband who has been providing me with the best environment for conducting my research over the years. I am also thankful to my son Yiming for being such a delightful little boy, who has been my source of joy in the arduous journey of pursuing my academic research.

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Contents

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1 1 2 4 4 5 6 6

2 Issues and Approaches to CTIS . . . . . 2.1 Major Issues and Findings in CTIS 2.2 Research Approaches to CTIS . . . . 2.3 Translation Styles in CTIS . . . . . . 2.4 Summary . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . .

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3 Translation Style in Sight Translation . . . . . . . . . . . . . . . . . 3.1 Concept of Translation Style . . . . . . . . . . . . . . . . . . . . . . 3.2 Sight Translation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.3 Global Behavioral Styles . . . . . . . . . . . . . . . . . . . . . . . . . 3.3.1 Behaviors in Different Stages . . . . . . . . . . . . . . . . 3.3.2 Interaction Between Behaviors . . . . . . . . . . . . . . . 3.3.3 Coordination Behaviors . . . . . . . . . . . . . . . . . . . . 3.4 Local Behavioral Styles . . . . . . . . . . . . . . . . . . . . . . . . . 3.4.1 Problem Identification Behaviors . . . . . . . . . . . . . 3.4.2 Problem-Solving Behaviors . . . . . . . . . . . . . . . . . 3.4.3 Problem Triggers and Coordination Behaviors . . . . 3.5 Behavioral Styles of Novice and Professional Interpreters . 3.6 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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1 Introduction . . . . . . . . . . . . . . . . . . . 1.1 Research Purpose and Motivation 1.2 Research Background . . . . . . . . . 1.3 Research Questions . . . . . . . . . . . 1.4 Significance of the Study . . . . . . 1.5 Structure of the Book . . . . . . . . . 1.6 Summary . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . .

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4 Eye-Tracking Method . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.1 Eye-Tracking Indicators . . . . . . . . . . . . . . . . . . . . . . . . . . 4.2 Data Collection . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.2.1 Participants . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.2.2 Materials . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.2.3 Apparatus and Presentation of Stimuli . . . . . . . . . . . 4.2.4 Procedure . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.3 Data Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.3.1 Eye Data Quality . . . . . . . . . . . . . . . . . . . . . . . . . . 4.3.2 General Guidelines for Conducting LMER Analysis 4.3.3 Data Analysis for Global Style 1 . . . . . . . . . . . . . . 4.3.4 Data Analysis for Global Style 2 . . . . . . . . . . . . . . 4.3.5 Data Analysis for Global Style 3 . . . . . . . . . . . . . . 4.3.6 Data Analysis for Local Style 1 . . . . . . . . . . . . . . . 4.3.7 Data Analysis for Local Style 2 . . . . . . . . . . . . . . . 4.3.8 Data Analysis for Local Style 3 . . . . . . . . . . . . . . . 4.4 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Appendix . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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5 Global and Local Styles of Sight Translation . . . . . . . . . . . 5.1 Eye-Movement Behaviors . . . . . . . . . . . . . . . . . . . . . . . 5.1.1 Overall Gaze Patterns . . . . . . . . . . . . . . . . . . . . 5.1.2 Task Time . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.1.3 Fixation Count . . . . . . . . . . . . . . . . . . . . . . . . . 5.1.4 Saccadic Amplitude . . . . . . . . . . . . . . . . . . . . . . 5.1.5 Fixation Duration . . . . . . . . . . . . . . . . . . . . . . . . 5.1.6 Pupil Dilation . . . . . . . . . . . . . . . . . . . . . . . . . . 5.1.7 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.2 Gaze Behaviors in Actual Sight Translation . . . . . . . . . . 5.2.1 Effect of TT1 on TT2 . . . . . . . . . . . . . . . . . . . . 5.2.2 Effect of FC1 on FC2 . . . . . . . . . . . . . . . . . . . . 5.2.3 Effect of SA1 on SA2 . . . . . . . . . . . . . . . . . . . . 5.2.4 Effect of FD1 on FD2 . . . . . . . . . . . . . . . . . . . . 5.2.5 Effect of PD1 on PD2 . . . . . . . . . . . . . . . . . . . . 5.2.6 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.3 Coordination Behaviors as Reflected via EVS . . . . . . . . 5.3.1 Maximum EVS at Textual Level . . . . . . . . . . . . 5.3.2 Minimum EVS at Textual Level . . . . . . . . . . . . . 5.3.3 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.4 Problem Identification Behaviors . . . . . . . . . . . . . . . . . . 5.4.1 Classification, Location, and Features of Potential Problems . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.4.2 Cognitive Load of Common Potential Problems .

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Contents

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5.4.3 Interaction Between Potential Problems and Subject Groups on Cognitive Load . . . . . . . . . . . . . . . . . . . . . 5.4.4 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.5 Problem-Solving Behaviors . . . . . . . . . . . . . . . . . . . . . . . . . . 5.5.1 Types of Problem-Solving Processes . . . . . . . . . . . . . . 5.5.2 Problem-Solving Behaviors as Indicated by Eye Measures . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.5.3 Problem-Solving Behaviors as Indicated by Eye Measure and Translation Output . . . . . . . . . . . 5.5.4 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.6 Coordination Behaviors as Reflected via EVS and Translation Problems . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.6.1 Descriptive Statistics of EVS at Word Level . . . . . . . . 5.6.2 Problem Effect on Maximum EVS . . . . . . . . . . . . . . . 5.6.3 Interaction Between Translation Problems and Subject Groups on EVS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.6.4 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.7 Summary of the Chapter . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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6 Gaze Behaviors, Interpreting Styles, and Language Specificity . . 6.1 Gaze Behaviors in Preparation and in Actual Sight Translation 6.2 Impact of Gaze Behaviors . . . . . . . . . . . . . . . . . . . . . . . . . . . 6.3 Global Coordination Styles . . . . . . . . . . . . . . . . . . . . . . . . . . 6.4 Problem Identification Behaviors . . . . . . . . . . . . . . . . . . . . . . 6.5 Problem-Solving Behaviors . . . . . . . . . . . . . . . . . . . . . . . . . . 6.6 Local Coordination Styles . . . . . . . . . . . . . . . . . . . . . . . . . . . 6.7 Eye-Movement Behaviors and Language Pairs . . . . . . . . . . . . 6.8 Eye-Tracking Methodology . . . . . . . . . . . . . . . . . . . . . . . . . . 6.9 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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7 Looking Ahead . . . . . . . . . . . . . 7.1 Summary of Major Findings 7.2 Implications . . . . . . . . . . . . 7.3 Concluding Remarks . . . . . . 7.4 Future Research . . . . . . . . .

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Index . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 157

Abbreviations

AOI CANP CANPFBG CAP CAPFBG CI CPNP CPNPFBG CPP CPPFBG CSI CTIS EEG EKS EVS FC FD FFD fMRI fNIRS LMER Max. EVS Min. EVS PD SA SI TA

Area of interest Common actual non-problem Common actual non-problem for both groups Common actual problem Common actual problem for both groups Consecutive interpreting Common potential non-problem Common potential non-problem for both groups Common potential problem Common potential problem for both groups Culture-specific items Cognitive translation and interpreting studies Electroencephalography Eye-key span Eye-voice span Fixation count Fixation duration First fixation duration Functional magnetic resonance imaging Functional near-infrared spectroscopy Linear mixed-effects regression modeling Maximal eye-voice span Minimal eye-voice span Pupil dilation Saccade amplitude Simultaneous interpreting Think aloud

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TAPs TFD TPR TT

Abbreviations

Think-aloud protocols Total fixation duration Translation process research Task time

List of Figures

Fig. Fig. Fig. Fig. Fig. Fig. Fig. Fig. Fig. Fig. Fig. Fig. Fig. Fig. Fig. Fig. Fig. Fig.

4.1 5.1 5.2 5.3 5.4 5.5 5.6 5.7 5.8 5.9 5.10 5.11 5.12 5.13 5.14 5.15 5.16 5.17

Fig. 5.18 Fig. 5.19

Project structures in Tobii Studio . . . . . . . . . . . . . . . . . . . . . . Interaction effect plot between stage and group on TT . . . . . . Interaction effect plot between stage and group on FC . . . . . . Interaction effect plot between stage and group on SA . . . . . . Interaction effect plot between stage and group on FD . . . . . . Interaction effect plot between stage and group on PD . . . . . . Effect plot of TT1 on TT2 for novices . . . . . . . . . . . . . . . . . . Effect plot of TT1 on TT2 for professionals . . . . . . . . . . . . . . Effect plot of FC1 on FC2 for novices . . . . . . . . . . . . . . . . . . Effect plot of FC1 on FC2 for professionals . . . . . . . . . . . . . . Effect plot of SA1 on SA2 for novices . . . . . . . . . . . . . . . . . . Effect plot of SA1 on SA2 for professionals. . . . . . . . . . . . . . Effect plot of FD1 on FD2 for novices . . . . . . . . . . . . . . . . . . Effect plot of FD1 on FD2 for professionals. . . . . . . . . . . . . . Effect plot of PD1 on PD2 for novices . . . . . . . . . . . . . . . . . . Effect plot of PD1 on PD2 for professionals. . . . . . . . . . . . . . Partial effect plot of Max. EVS at the textual level. . . . . . . . . Translation progression graph of P03 when sight translating Text 3. The gray dots represent fixations on the source text word. The black dots represent the output word that was mapped onto the corresponding source text word. The larger gray dots represent longer fixation duration, and the larger black dots represent longer voice duration of each output word. The double brackets represent the activities of reading ahead and uttering the translation in parallel . . . . . . . . . . . . . . . . . . . Translation progression graph of N04 when sight translating Text 4 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Partial effect plot of Min. EVS at the textual level . . . . . . . . .

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Fig. Fig. Fig. Fig. Fig. Fig. Fig.

List of Figures

5.20 5.21 5.22 5.23 5.24 5.25 5.26

Fig. 5.27

Fig. 5.28 Fig. 5.29 Fig. 5.30

Fig. 5.31 Fig. 5.32

Fig. 5.33

Fig. 5.34 Fig. 5.35 Fig. 5.36 Fig. 5.37 Fig. 5.38

Effect plot of CPP on FFD for novices . . . . . . . . . . . . . . . . . . Effect plot of CPP on TFD for novices. . . . . . . . . . . . . . . . . . Effect plot of CPP on FFD for professionals . . . . . . . . . . . . . Effect plot of CPP on TFD for professionals . . . . . . . . . . . . . Interaction effect plot between AOI and group on FFD . . . . . Interaction effect plot between AOI and group on TFD . . . . . Comparative density plot of Max. EVS at a word level. The solid line represents the density curve of novices, and the dashed line represents the density curve of professionals . . . . Comparative density plot of Min. EVS at a word level. The solid line represents the density curve of novices, and the dashed line represents the density curve of professionals . . . . Partial effect plots of Max. EVS at the word level in the group of novices . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Partial effect plot of Max. EVS at the word level in the group of professionals . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Translation progression graph of N12 when sight translating the segment ranging from word 12 to word 21 of Text 1. The blue dots represent fixations on the source text word. The orange dots represent the output words. The larger blue dots represent longer fixation duration, and the larger orange dots represent longer voice duration of each output word . . . . . . . Translation progression graph of P01 when sight translating the segment ranging from word 100 to word 111 of Text 2 . . Pie chart of the time N12 spent on each production activity as percentage of the Max. EVS of the problem word “共同体” in Text 1 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Pie chart of the time P01 spent on each production activity as a percentage of the duration of the Max. EVS of the problem word “乘势而上” in Text 2 . . . . . . . . . . . . . . . . . . . . . . . . . . Translation progression graph of P05 when sight translating the segment ranging from word 84–93 of Text 4 . . . . . . . . . . Partial effect plot of Min. EVS at the word level in the group of novices . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Partial effect plot of Min. EVS at the word level in the group of professionals . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Partial interaction effect plots between AOI and group of Max. EVS at the word level . . . . . . . . . . . . . . . . . . . . . . . . Partial interaction effect plots between AOI and group of Min. EVS at the word level . . . . . . . . . . . . . . . . . . . . . . . .

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List of Figures

Fig. 6.1

Fig. 6.2

Fig. 6.3 Fig. 6.4

Scanpath of N05 during the preparatory reading. The circles represent eye fixations. The lines that connect the circles represent saccades. The longer the line, the longer the saccade . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Scanpath of P08 when reading the source text in the actual sight translation. The circles represent eye fixations. The lines that connect the circles represent saccades. The longer the line, the longer the saccade . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Translation progression graph of N05 when sight translating the segment in Table 6.2 . . . . . . . . . . . . . . . . . . . . . . . . . . . . Translation progression graph of P04 when sight translating the segment in Table 6.2 . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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List of Tables

Table 3.1 Table Table Table Table

4.1 4.2 4.3 4.4

Table 4.5 Table 4.6 Table 4.7 Table 5.1

Table 5.2 Table Table Table Table Table Table Table Table Table Table Table Table Table Table Table

5.3 5.4 5.5 5.6 5.7 5.8 5.9 5.10 5.11 5.12 5.13 5.14 5.15 5.16 5.17

Preparation time and materials in the research of prepared sight translation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Research questions and their indicators . . . . . . . . . . . . . . . . Profile of the Novice Interpreters . . . . . . . . . . . . . . . . . . . . . Profile of the professional interpreters . . . . . . . . . . . . . . . . . Language proficiency and translation competence of participants . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Text profiling . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Percentage of valid gaze samples . . . . . . . . . . . . . . . . . . . . . Classification of what potential problems in stage 1 would be like in stage 2 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Means and standard deviations for time and the eye measures in preparation and actual sight translation by each participant . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Means and standard deviations for time and the eye measures between novices and professionals across the two stages . . . Means for TT (min) of each group in each stage . . . . . . . . . LMER results of TT model . . . . . . . . . . . . . . . . . . . . . . . . . Pairwise comparisons of interaction effect on TT . . . . . . . . . Means for FC of each group in each stage. . . . . . . . . . . . . . LMER results of FC model . . . . . . . . . . . . . . . . . . . . . . . . . Pairwise comparisons of interaction effect on FC . . . . . . . . . Means for SA (degree) of each group in each stage. . . . . . . LMER results of SA model . . . . . . . . . . . . . . . . . . . . . . . . . Means for FD (ms) of each group in each stage . . . . . . . . . LMER results of FD model . . . . . . . . . . . . . . . . . . . . . . . . . Means for PD (mm) of each group in each stage . . . . . . . . . LMER results of PD model . . . . . . . . . . . . . . . . . . . . . . . . . LMER results of TT1–TT2 model for novices . . . . . . . . . . . LMER results of TT1–TT2 model for professionals . . . . . . LMER results of FC1–FC2 model for novices . . . . . . . . . . .

. . . .

25 50 51 52

.. .. ..

52 53 56

..

62

..

70

. . . . . . . . . . . . . . . .

71 71 71 72 73 73 74 75 75 76 77 78 78 81 81 82

. . . .

. . . . . . . . . . . . . . . .

xix

xx

Table Table Table Table Table Table Table Table

List of Tables

5.18 5.19 5.20 5.21 5.22 5.23 5.24 5.25

Table 5.26 Table 5.27 Table 5.28 Table 5.29 Table 5.30 Table 5.31 Table 5.32 Table 5.33 Table 5.34 Table Table Table Table Table

5.35 5.36 5.37 5.38 5.39

Table 5.40 Table Table Table Table

5.41 5.42 5.43 5.44

Table 5.45 Table 5.46 Table 5.47

LMER results of FC1–FC2 model for professionals . . . . . . LMER results of SA1–SA2 model for novices . . . . . . . . . . LMER results of SA1–SA2 model for professionals . . . . . . LMER results of FD1–FD2 model for novices . . . . . . . . . . LMER results of FD1–FD2 model for professionals . . . . . . LMER results of PD1–PD2 model for novices . . . . . . . . . . LMER results of PD1–PD2 model for professionals . . . . . . Means and standard deviations between novices and professionals for Max. and Min. EVS (ms) at the textual level . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . LMER results of Max. EVS model at the textual level . . . . LMER results of Min. EVS model at the textual level . . . . . CPPs identified by the novice interpreters in the preparatory reading . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . CPPs identified by the professional interpreters in the preparatory reading . . . . . . . . . . . . . . . . . . . . . . . . . . Classification and number of CPPs . . . . . . . . . . . . . . . . . . . Number of CPPs in the first and second half of the source texts . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Potentially problematic four-character expressions for novices . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Potentially problematic four-character expressions for professionals . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Means of FFD (ms) and TFD (ms) on CPPs and CPNPs in each group . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . LMER results of FFD model for novices . . . . . . . . . . . . . . . LMER results of TFD model for novices . . . . . . . . . . . . . . . LMER results of FFD model for professionals . . . . . . . . . . LMER results of TFD model for professionals . . . . . . . . . . Means for FFD (ms) on CPPFBGs and CPNPFBGs in each group . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Means for TFD (ms) on CPPFBGs and CPNPFBGs in each group . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . LMER results of FFD model . . . . . . . . . . . . . . . . . . . . . . . . LMER results of TFD model . . . . . . . . . . . . . . . . . . . . . . . . Types of problem-solving processes . . . . . . . . . . . . . . . . . . . Number and percentage of Type 1 and Type 2 problem-solving processes . . . . . . . . . . . . . . . . . . . . . . . . . . Number and percentage of the subtypes of problem-solving processes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Number and percentage of major and minor errors, disfluencies and omissions . . . . . . . . . . . . . . . . . . . . . . . . . . Number and percentage of meaning and expression errors. .

. . . . . . .

82 83 84 84 84 85 85

.. .. ..

87 88 91

..

94

.. ..

95 95

..

95

..

96

..

96

. . . . .

96 97 97 98 99

. . . . . . .

. . . . .

. . 100 . . . .

. . . .

100 101 101 104

. . 104 . . 106 . . 107 . . 107

List of Tables

Table 5.48 Table 5.49 Table 5.50

Table 5.51 Table 5.52 Table 5.53 Table 5.54 Table 5.55 Table 5.56 Table 5.57 Table 5.58 Table 6.1 Table 6.2

xxi

CAPs identified by the novice interpreters in the actual sight translation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . CAPs identified by the professional interpreters in the actual sight translation . . . . . . . . . . . . . . . . . . . . . . . . Means and standard deviations between novices and professionals for Max. and Min. EVS (ms) on CAPs and CANPs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . LMER results of Max. EVS model at word level for novices . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . LMER results of Max. EVS model at a word level for professionals . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . LMER results of Min. EVS model at a word level for novices . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . LMER results of Min. EVS model at a word level for professionals . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Means for Max. EVS (ms) of each group on CAPFBG and CANPFBG . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . LMER results of Max. EVS model at a word level for both groups . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Means for Min. EVS (ms) of each group on CAPFBG and CANPFBG . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . LMER results of Min. EVS model at a word level for both groups . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Structure of “modifier + de + noun” in Chinese . . . . . . . . . Segment (“中国特色社会主义取得的成就”) with structure of “modifier + de + noun” in Chinese . . . . . . . . . . . . . . . . .

. . 110 . . 111

. . 111 . . 112 . . 112 . . 120 . . 121 . . 121 . . 122 . . 123 . . 123 . . 140 . . 142

Chapter 1

Introduction

Abstract This chapter will first outline the purpose and motivation of the present project in Sect. 1.1. This is followed by a review of the research background, a description of the form of sight translation used in the present study, and a definition of the concept of global and local styles in Sect. 1.2. Six research questions are raised: three related to the global aspects of translation styles, the other three to the local aspects of translation styles in Sect. 1.3. Significance of the study and structure of the book are presented in Sects. 1.4 and 1.5, respectively. The chapter ends with a summary in Sect. 1.6. Keywords Sight translation · Global styles · Local styles

1.1 Research Purpose and Motivation Sight translation is an important interpreting mode in professional and pedagogical scenarios (De Laet 2012). It is also a highly informative modality for probing into moment-to-moment cognitive processing during a language transfer (Shreve et al. 2010). However, interpreters’ behaviors and the underlying cognitive processes in sight translation are still underexplored. This study is an attempt to examine the behaviors, or translation styles, of novice and professional interpreters when performing sight translation from Chinese into English. Furthermore, this study seeks to identify which translation styles are shared or specific to each group using eye-tracking measures and indicators of interpreting outputs. The study also aims to explore behavioral styles that pertain to the Chinese– English language pair. Due to the fact that the cognitive aspects of Chinese translation—especially sight translation when using eye-tracking as the research method— are still underexplored, it would well be very important to identify behavioral patterns that are specific to the Chinese–English language pair. By providing detailed procedures from the model selection to the interpretation of results, the study intends to encourage the application of linear mixed-effects regression modeling (LMER) to the empirical, experimental approach of cognitive translation and interpreting studies (CTIS). © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2020 W. Su, Eye-Tracking Processes and Styles in Sight Translation, New Frontiers in Translation Studies, https://doi.org/10.1007/978-981-15-5675-3_1

1

2

1 Introduction

The motivation of the present project is threefold. First, the eye-tracking technique as a research tool has been systematically applied to translation and interpreting studies since the seminal research of O’Brien (2007), in which she used eye-tracking measures to examine the cognitive load caused by different match types of translation memory tools. The past decade has indeed witnessed an upsurge in translation studies using the eye-tracking methodology, but few have attempted to investigate eye-movement behaviors in the process of sight translation specifically. Since reading behaviors constitute an essential part of sight translation, further exploration of the reading behaviors via eye-movement patterns during sight translation could bring some key insights to the field. Secondly, previous research has shown that language-pair specificity affects eyemovement patterns in sight translation (e.g., Rojo and Valenzuela 2013; Chmiel and Lijewska 2019). However, among the studies that examined eye-movement patterns in sight translation, the Chinese and English language pair has again been little studied (cf. Su and Li 2019). As such, the present study uses discourses with Chinese characteristics as the source texts of sight translation to investigate how reading behaviors are affected by the Chinese–English language pair. Thirdly, as Martínez-Gómez et al. (2018) aptly stated, “it is crucial in TPR [translation process research] to elucidate what types of translator behaviors there are, in what occasions they occur, and how different behavioral patterns correlate with the final translation product” (p. 99). The investigation of translators’ and interpreters’ behaviors in different modes of translation and interpreting is indeed one of the major issues in CTIS, and the interaction between behaviors and output performance helps in the understanding of how translators and interpreters arrive at their final products. Therefore, the first step is to identify and classify behavioral patterns before addressing the relationship between processing styles and translation products in future studies.

1.2 Research Background Thanks to technological advances, such as keystroke logging, eye-tracking and neuroimaging technologies (Su and Li 2018), CTIS has seen rapid growth over the past decades, with research having been conducted on the psycholinguistic, cognitive, and neurocognitive aspects of translation and interpreting. This study aims to explore the issue of translation style by adopting a behavioral–cognitive approach to investigate interpreters’ behaviors and their styles of processing in sight translation, and how these behaviors relate to their interpreting experience. The classification of translators’ and interpreters’ behaviors during translation and interpreting will contribute to the understanding of translation styles. The investigation of translation styles is interesting in itself because it allows for an exploration of the possible behavioral patterns when translators or interpreters perform a translation or interpreting task and an identification of the cognitive processes behind these patterns.

1.2 Research Background

3

However, in CTIS, only a few studies have specified translation style as their main research focus (e.g., Asadi and Séguinot 2005; Alves and Vale 2011; Dragsted and Carl 2013), of which they have all centered around the styles in written translation, mostly between European languages. This study seeks to fill this gap through an investigation of the translation styles of novice and professional interpreters in sight translation—an underexplored modality. To this end, discourse with Chinese features is used as the task material. The study will also tap into the cognitive processes of sight translation based on the behavioral styles. To achieve this, the present study adopts the eye-tracking technique as the main instrument to collect the data. This will be the first effort to study translation styles in the mode of sight translation between Chinese and English, two vastly different languages. In the present study, participants were given time to pre-read the source text that was to be subsequently sight translated. This form of sight translation is known as rehearsed sight translation (Sandrelli 2003) or simply prepared sight translation. For the sake of analysis, sight translation was examined in two major stages: advance preparation and the subsequent actual sight translation. Preparation was defined as the period of time when participants began their silent reading of the source text until they felt ready to render the source text orally. Advance preparation was immediately followed by actual sight translation, where participants started uttering the renditions of the source text until they considered their sight translation of the whole text finished. Translation style was investigated in terms of global and local styles. Global styles referred to the general behavioral patterns of interpreters when performing sight translation. Global styles were characterized by eye-movement behaviors at the textual level. Local styles referred to more specific behavioral characteristics of interpreters in sight translation and were characterized by eye-movement behaviors at the lexical level. The combination of global and local perspectives offered a comprehensive and thorough description of behavioral styles in sight translation. Specifically, eye measures at the textual level were used for describing global and general behavioral characteristics, whereas eye measures at the lexical level were applied to the identification of translation problems encountered by interpreters and to the investigation of how these problems were addressed. Triangulating eye-tracking data with output analysis was needed to enable a full and comprehensive understanding of how interpreters coped with problem triggers. Moreover, the measure of eye-voice span (EVS) was a key tool when addressing the issue of coordination between reading and speaking in sight translation. EVS at the textual level was used to examine global coordination behaviors, whereas EVS at the lexical level was employed to investigate how reading-speech coordination was influenced by local problem triggers.

4

1 Introduction

1.3 Research Questions To ensure the study was focused, the following questions were used to guide the project. The overall research question was what are the global and local styles of translation in Chinese–English sight translation of a discourse with Chinese features? More specifically, for global translation styles, the following research questions were proposed: (1) How are eye-movement behaviors affected by the two different stages of sight translation? Do novice and professional interpreters exhibit different gaze behaviors in each of the two stages? (2) How do the gaze behaviors displayed in advance preparation affect the gaze behaviors exhibited in the subsequent actual sight translation? Does the influence vary between novice and professional interpreters? (3) How do novice and professional interpreters coordinate reading and speaking in actual sight translation, as measured by EVS at the textual level? For local translation styles, the following research questions were addressed: (4) What common potential problems in advance preparation can be identified for novice and professional interpreters? (5) What happens to potential problem triggers in actual sight translation? Do novice and professional interpreters display different behaviors when solving the potential problems in actual sight translation? (6) How do translation problems affect coordination styles? To answer these questions, a behavioral–cognitive approach was adopted. The eyetracking technology was used to record the eye-movement behaviors of the research participants.

1.4 Significance of the Study The investigation of behavioral styles in sight translation from Chinese into English offers four major contributions to the field. First, this is one of the first studies that focuses on the behavioral aspects of sight translation. The study used eye measures at a textual and lexical level to describe the global and local dimensions of behavioral styles in sight translation and examined gaze behaviors—from problem identification, problem-solving, to coordination between reading and speaking—in preparation and actual sight translation. As the study is intrinsically dedicated to a comprehensive description of eye-movement behaviors in sight translation, it seeks to contribute to the understanding of sight translation from the behavioral, process perspective. Second, this study’s use of an innovative methodology in its investigation is in itself significant. The eye-tracking method is still relatively new in translation and interpreting studies, especially in the modality of spoken translation such as sight translation and simultaneous interpreting (SI). However, acquiring information from

1.4 Significance of the Study

5

the eyes is an essential part of the translation and interpreting process, and the eyetracking method helps record eye movements as translators and interpreters process the information by offering online, objective data for researchers to analyze and understand their behaviors. Through the application of the eye-tracking method to the investigation of gaze behaviors in sight translation, the study demonstrates the usefulness of the eye-tracking method as a methodology in spoken translation. Furthermore, the indicators of translation styles derived from previous studies, and further developed in the present study, can serve as a reference for future research on behavioral styles in translation and interpreting. Third, the findings of the study will help us better understand the overall cognitive processes of Chinese–English translation, particularly sight translation between Chinese and English. The cognitive exploration of translation and interpreting between Chinese and English is still in its early stages, and concrete information on the process is scarce (e.g., Lin et al. 2018; Liu et al. 2019; Su and Li 2019). The findings related to gaze behaviors in sight translation from Chinese to English will add to the understanding of the cognitive processes of sight translation in general. Moreover, since Chinese (a logographic language) differs vastly from English (an alphabetic language), eye-movement behaviors are believed to exhibit particular patterns in the interpreting process of the Chinese–English language pair in comparison with European language pairs. Fourth, this study provides empirical evidence to confirm some of our intuitive understandings or suppositions of the differences between novice and professional interpreters. Behavioral styles common to both interpreter groups aside, the present study aims to identify behavioral differences in the process of sight translation and shed some light on how interpreting experience influences interpreting behaviors.

1.5 Structure of the Book The study aims to investigate the patterns of eye-movement behaviors emerging from the process of sight translation from Chinese to English and to explore different behavioral patterns between novice and professional interpreters. The book is comprised of seven chapters. Chapter 1 introduces the purpose and motivations behind investigating the behavioral styles of sight translation, outlines the background to the current research, proposes the research questions, and discusses the study’s potential contributions to the field. Chapter 2 provides the theoretical grounding for the investigation of behavioral styles using the eye-tracking method. This chapter presents four major research approaches to CTIS, summarizes the major issues and findings using these four approaches, and highlights the importance of adopting a behavioral approach to study translation styles in sight translation. Chapter 3 turns to the topic of the present study and reviews the existing literature on translation styles. It defines various translation styles and discusses how

6

1 Introduction

these were operationalized within behavioral–cognitive approaches to translation and interpreting studies. It then focuses on the operationalization of styles in sight translation. Chapter 4 gives detailed descriptions of the research design. It begins with the descriptions of data collection, covering details of research participants, experimental materials, apparatus, and the procedure of the experiment. It then discusses how the data collected in the experiment was processed and analyzed. Chapter 5 reports the results of the experiment. It presents the results of global translation styles, including eye-movement behaviors as a function of stage and group, correlations of gaze patterns between preparation and actual sight translation, and the overall pattern of reading-speech coordination. Once done, the chapter turns to local translation styles and presents their results, including the identification of potential problem triggers, problem-solving behaviors, and local coordination patterns as a function of translation problems. Chapter 6 discusses and interprets the results of behavioral styles in sight translation. It provides detailed explanations for each research question, followed by a discussion of the eye-tracking method and the role of language-pair specificity in gaze patterns of sight translation. Chapter 7 serves as the conclusion of the study. It summarizes the major findings of the translation styles, provides methodological, statistical and pedagogical implications, and discusses the limitations of the present study, as well as further research topics stemming from the present research of translation styles.

1.6 Summary This chapter has introduced the research topic of translation styles, including the research objectives and motivations for the investigation of behavioral styles in sight translation. The research background has been reviewed, research questions concerning global and local styles proposed, and the structure of the book has been outlined. I also discussed the major contributions of the study to the research on translation and interpreting.

References Alves, F., & Vale, D. C. (2011). On drafting and revision in translation: A corpus linguistics oriented analysis of translation process data. TC3: Translation: Computation, Corpora, Cognition, 1(1), 105–122. Asadi, P., & Séguinot, C. (2005). Shortcuts, strategies and general patterns in a process study of nine professionals. Meta, 50(2), 522–547. https://doi.org/10.7202/010998ar. Chmiel, A., & Lijewska, A. (2019). Syntactic processing in sight translation by professional and trainee interpreters: Professionals are more time-efficient while trainees view the source text less. Target, 31(3), 378–397.

References

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De Laet, F. (2012). Teaching and training sight translation: A multitasking activity. In W. Ren (Ed.), Interpreting in the age of globalization—Proceedings of the 8th National Conference and International Forum on Interpreting (pp. 181–198). Beijing: Foreign Language Teaching and Research Press. Dragsted, B., & Carl, M. (2013). Towards a classification of translation styles based on eye-tracking and keylogging data. Journal of Writing Research, 5(1), 133–158. https://doi.org/10.17239/jowr2013.05.01.6. Lin, X., Lei, V. L. C., Li, D., Zhishan, H., Xiang, Y., & Yuan, Z. (2018). Mapping the small-world properties of brain networks in Chinese to English simultaneous interpreting by using functional near-infrared spectroscopy. Journal of Innovative Optical Health Sciences, 11(03), 1–12. https:// doi.org/10.1142/S1793545818400011. Liu, Y., Zheng, B., & Zhou, H. (2019). Measuring the difficulty of text translation: The combination of text-focused and translator-oriented approaches. Target, 31(1), 125–149. https://doi.org/10. 1075/target.18036.zhe. Martínez-Gómez, P., Han D., Carl, M., & Aizawa A. (2018). Recognition and characterization of translator attributes using sequences of fixations and keystrokes. In C. Walker, & M. Federico Federici (Eds.), Eye tracking and multidisciplinary studies on translation (pp. 97–120). Amsterdam/Philadelphia: John Benjamins Publishing Company. O’Brien, S. (2007). Eye-tracking and translation memory matches. Perspectives, 14(3), 185–205. https://doi.org/10.1080/09076760708669037. Rojo, A., & Valenzuela, J. (2013). Constructing meaning in translation: The role of constructions in translation problems. In Ana Rojo & Iraide Ibarretxe-Antuñano (Eds.), Cognitive linguistics and translation: Advances in some theoretical models and applications (pp. 283–310). Berlin: De Gruyter Mouton. Sandrelli, A. (2003). New technologies in interpreter training: CAIT. In H. Gerzymisch-Arbogast, E. Hajicová, P. Sgall, Z. Jettmarová, A. Rothkegel, & D. Rothfuß-Bastian (Eds.), Textologie und translation (pp. 261–293). Tübingen: Gunter Narr. Shreve, G. M, Isabel, L., & Angelone, E. (2010). Cognitive effort, syntactic disruption, and visual interference in a sight translation task. In G. M. Shreve, & E. Angelone (Eds.), Translation and cognition (pp. 63–84). Amsterdam/Philadelphia: John Benjamins Publishing Company. Su, W., & Li, D. (2018). Translation process research: Current issues and methods—An interview with Prof. Arnt Lykke Jakobsen. Foreign Languages in China, 15(5), 102–111 [苏雯超, 李德凤. 2018. 翻译认知过程研究:现状、问题与方法—阿恩特·雅可布森教授访谈录. 《中国外语》 2015 (2015), 2102–2111]. Su, W., & Li, D. (2019). Identifying translation problems in English-Chinese sight translation: An eye-tracking experiment. Translation and Interpreting Studies, 14(1), 110–134. https://doi.org/ 10.1075/tis.00033.su.

Chapter 2

Issues and Approaches to CTIS

Abstract This chapter contextualizes translation styles in terms of CTIS and discusses how the investigation of translation styles using the eye-tracking methodology fits into the field. The chapter reviews the major issues and findings adopting the major research approaches to CTIS in Sect. 2.1 and outlines the four major research approaches to CTIS in Sect. 2.2. The topic of translation styles in the context of CTIS is related in Sect. 2.3. Keywords Translation styles · Research approaches to CTIS · Eye-tracking methodology

2.1 Major Issues and Findings in CTIS Since the second half of the twentieth century, translation studies have seen rapid growth to the point where many have claimed that it has become an independent discipline (Munday 2001). In its earlier days, translation studies mainly drew on theories from neighboring disciplines—most notably linguistics and literary studies (e.g., Nida and Taber 1969; Even-Zohar 1978/2000; Toury 1978/2000). The most recent development has seen the integration of, among others, computational linguistics, corpus linguistics, and cognitive neuroscience to the field of translation and interpreting (e.g., Li et al. 2011; Carl and Báez 2019; García 2019). Moreover, CTIS is perhaps the fastest growing area in translation and interpreting studies (Li et al. 2019). The central aim of CTIS is to understand the cognitive processes by which translators and interpreters arrive at their own translations and interpretations (Jakobsen 2017). Li (2017) outlined four major approaches to the investigation of how translators and interpreters carry out their professional tasks, namely psycholinguistic, behavioral, corpus-based, and neurological approaches. A rich array of issues has been studied using these four research approaches. While the implications of these studies are worth exploration and discussion, due to spatial constraint, this book must focus on the issues and findings that are more closely related to the present study of translation styles in sight translation. © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2020 W. Su, Eye-Tracking Processes and Styles in Sight Translation, New Frontiers in Translation Studies, https://doi.org/10.1007/978-981-15-5675-3_2

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2 Issues and Approaches to CTIS

Studies using think aloud (TA) within the psycholinguistic approach mainly investigate translation problems and strategies in translation and interpreting processes (e.g., Lörscher 1991; Ivanova 2000; Atari 2005; Künzli 2009; Araghian et al. 2018), as these two issues are what the majority of think-aloud protocols (TAPs) examine during the processes of translation and interpreting tasks (Krings 1986). Although these TA studies do not explicitly state translation styles to be the focus of their research, what they actually examine is closely related to what is termed as translation styles in CTIS today. As Breedveld points out, “the analysis of TAPs very often results in the description of overall characteristics of the processes of individual translators or proficiency groups of translators” (2002, p. 221). Based on the linguistic manifestations in verbal protocols, the majority of TA studies analyze the common problems encountered, and the strategies employed, by professionals throughout translation processes, and how these problems and strategies are related to other factors, such as directionality and experience, with the purpose of describing the regularities and trends of translation processes. One tentative finding of TA studies is that some problem-solving behaviors are shared by different interpreter groups, while others are influenced by specific translation and interpreting experiences. For example, in simultaneous interpreting (SI), omitting the source text was found to be a common strategy among interpreters experiencing difficulties (Tiselius and Jenset 2011). Professional translators tend to address problems in an immediate context, whereas beginners focus on problems at a word level in written translation (Angelone 2010). In consecutive interpreting (CI), novice interpreters frequently omit information in the target text, while professional interpreters tend to prefer adding information to their interpretations (Wang and Li 2015). One major issue of the corpus-based approach to CTIS is the investigation of processing paths. By investigating how culture specific items (CSI) are translated and interpreted based on a bilingual parallel corpus comprising both source and target texts, this line of research observes the patterns of translation strategies (e.g., their frequency) and associates these patterns with cognitive processing routes (He 2019). Based on the analysis of a self-built SI corpus, Lang et al. (2019) found that the pairing strategy was most frequently used for the interpretation of proper names in CSIs, whereas strategies such as paraphrasing were most frequently used for the interpretation of non-proper names, such as idioms and metaphors in CSIs. They concluded that interpreting non-proper names, such as idiomatic expressions, required a higher cognitive load than interpreting proper names since paraphrasing required conceptual mediation, which is believed to involve a greater effort. It must be clarified that translator styles in corpus-based translation studies as described by Baker (2000)—which generally refers to the analysis of the idiosyncratic linguistic features of a translator (see more details in Sect. 3.1)—are not the focus of the corpus-based approach to translation and interpreting processes as discussed here. Translation styles in the CTIS context refer specifically to the patterns of cognitive processing displayed by translators and interpreters in the process of their tasks.

2.1 Major Issues and Findings in CTIS

11

In the neurological approach to CTIS, one of the research foci is the identification of the series of interacting networks of brain regions during SI in order to gain a deeper understanding of these neural mechanisms as an extremely challenging case of language processing (e.g., Rinne et al. 2000; Tommola et al. 2000; Hervais-Adelman et al. 2015). Neuroimaging studies have strongly indicated that SI processing not only involves language networks but also networks of cognitive control due to interpreters having to manage producing the target text while concurrently processing the source text (Hervais-Adelman et al. 2015; Elmer and Kühnis 2016). The findings imply that SI is a process of transferring meaning as well as a process of controlling actions, such as inhibiting production of non-target language and monitoring translation outputs. The behavioral approach to CTIS has the impact of translators’ behaviors in written translation as its primary focus (Dragsted and Carl 2013; Huang 2018; Feng 2019; Angelone 2019; Hvelplund 2019; Schaeffer et al. 2019; Lu et al. 2020), but there is a burgeoning interest in the investigation of interpreters’ gaze behaviors in spoken translation, such as SI and CI, with different types of visual input (Seeber 2017; Korpal and Stachowiak-Szymczak 2018, 2020; Stachowiak-Szymczak 2019; Stachowiak-Szymczak and Korpal 2019; Chmiel et al. 2020) and sight translation (Ho 2017; Ma 2019; Chmiel and Lijewska 2019; Su and Li 2019). One major research issue associated with behavioral patterns in sight translation is how eye-movement behaviors are affected by lexical or syntactic difficulties. Lexical difficulties are most typically operationalized by source text words that may cause interpreting problems for sight translators, whereas syntactic difficulties are often operationalized by source text syntax that requires reordering or reconstruction in the target language. A number of studies have reported that problematic words and syntax tend to increase fixation times in sight translation between different language pairs, including German, Polish and English (Korpal 2012), Polish and Russian (Płu˙zyczka 2013), English and Spanish (Rojo and Valenzuela 2013), and Chinese and English (Ma 2019; Su and Li 2019). For example, Su and Li (2019) found that visit durations significantly increased when student interpreters processed lexical problems, such as abstract nouns, and low frequency words and segmental problems, such as head-initial and head-final noun phrases in bi-directional sight translation. Longer fixations caused by difficult words and syntax indicate that interpreters deploy more cognitive and attentional resources when processing problematic information in sight translation. Another research issue within the behavioral approach to sight translation concerns how eye-movement behaviors are influenced by experience within the profession. This line of research examines whether interpreters with varying degrees of experience exhibit different gaze behaviors in sight translation. Although studies have shown that professional interpreters have a higher output quality than novices in SI (Liu et al. 2004; Díaz-Galaz et al. 2015), SI with PowerPoint presentations (Korpal and Stachowiak-Szymczakand 2018) and sight translation (Lee 2012), their behavioral differences—especially differences in gaze behaviors—are far from conclusive. Findings relevant to this line of inquiry will be discussed in Sect. 3.5.

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2.2 Research Approaches to CTIS As mentioned in Sect. 2.1, the investigation of translation and interpreting processes has predominantly relied on four research approaches, namely psycholinguistic, behavioral, corpus-based, and neurological. This section briefly describes each of these four research approaches, including their theoretical assumptions and limitations. The psycholinguistic approach adopts methods widely used in psychology or psycholinguistics, such as think aloud (TA), to collect participants’ verbal data during their performance of a translation task. This verbal data is recorded and then transcribed into think-aloud protocols (TAPs). Ericsson and Simon (1980) classified TA into two types: concurrent and retrospective. In concurrent TA, translators verbalize their thoughts while completing their task, whereas in retrospective TA, translators recall and verbalize the mental processes that occurred to them in an earlier translation task. Retrospective TA is usually applied in spoken translation. The theoretical assumption of TA is that information stored in short-term memory is directly accessible for verbalization, and “verbalization of thoughts per se” (Bowles 2010, p. 14) does not change cognitive processing. The predominant use of TAPs as a means of data elicitation is generally considered to characterize the first phase of CTIS (Alves and Albir 2017). However, some studies have shown that concurrent TA can delay the translation process (Jakobsen 2003), and retrospective TA may only reflect part of the process because of many problems and difficulties occurring during the process of translation and interpreting go unreported in the retrospective verbal reports (Englund Dimitrova and Tiselius 2014). Besides, translators may be unable to verbalize their thoughts in automated processing or when the translation itself is unproblematic. As a result, this kind of processing may not be captured in TAPs, something which Jakobsen considered “a serious problem with TA methodology” (2017, p. 28). To combat the so-called weaknesses of TAPs, keystroke logging technology was applied into TPR (Jakobsen and Schou 1999). It can record every keystroke produced by translators and thus reflects both automatic and non-automatic processing during translation. The use of keystroke logging together with other recording technologies, such as screen or video and, most recently, eye-tracking, can perhaps be called the behavioral approach to CTIS when triangulated with verbal data from TAPs and/or retrospective interviews. The most important theoretical assumption of the behavioral approach to CTIS is the “mind–brain–behavior correlation” (Jakobsen 2017, p. 22). This correlation assumes that one can make inferences about the cognitive processes from what can be observed and measured from the brain and behaviors during translation, such as typing activities and eye movements. Specifically, TPR using the eye-tracking method rests on the immediacy and eye-mind assumptions (Just and Carpenter 1980). The immediacy assumption refers to the idea that the mind immediately processes what the eyes see, while the eye-mind assumption states that what the eyes are looking at is what the mind is processing. The investigation of translators’ and interpreters’

2.2 Research Approaches to CTIS

13

behaviors during translation and interpreting characterizes the second and third phase of CTIS, with the second phase being characterized by keystroke logging as the primary research method and the third phase by the eye-tracking technology as the main research methodology (Alves and Albir 2017). Along with the development of keystroke logging in the 1990s, corpus technology has also been used to investigate translated language and infer from it the processes of translation (Baker 1993). Although Baker’s paper in 1993 sparked great interest in corpus-based translation studies, the application of corpora to translation process research, i.e., the corpus-based approach to CTIS, is relatively new (Rodríguez-Inés 2017). Within this approach, researchers make use of corpora that contain product and process data (e.g., keylogging data and/or eye-tracking data) (Alves and Vale 2011; Carl and Kay 2011), or product data (Lang et al. 2019), to probe and gain insights into the cognitive processes during translation and interpreting. With regard to the relation between cognitive processes and corpora of translation product data, it is theoretically assumed that patterns of translated texts can reveal aspects of the cognitive processes that led to them (Rodríguez-Inés 2017). For example, translation universals might suggest an asymmetry in the entrenched linguistic knowledge imprinted onto one’s brain, meaning that some semantic structures are more cognitively salient than others and are thus more frequently chosen by translators (Halverson 2003). In addition to this, translation strategies as observed in parallel corpora may reflect different processing paths (He 2019). It remains to be seen to what extent the corpus data—especially the offline translation or interpreting product data—can reveal online cognitive processes during translation and interpreting. It is not feasible to gain deep insights into the cognitive processes during translation based on corpus data as a single source (Heylen et al. 2008). In order to make more direct inferences about cognitive processes during translation, the corpus-based approach is perhaps better off when combined with other methods, such as keylogging and eye-tracking. The burgeoning interest in understanding the neural mechanisms underlying translation and interpreting is what aptly characterizes the fourth phase of CTIS (Li 2017). The neurological approach applies neurophysiological techniques such as electroencephalography (EEG) or neuroimaging methods such as functional nearinfrared spectroscopy (fNIRS) and functional magnetic resonance imaging (fMRI). These tools are used to examine the brain activation of bilingual and multilingual participants, including interpreters, in tasks associated with translation and interpreting processes, in an attempt to correlate brain activity with cognitive functions. The neurological approach relies on the assumption that cognitive processes recruit partially specific distributed neural circuits and involve measurable hemodynamic, electrical, and chemical changes (García 2019). To apply neurological technologies to examine cognitive processes during translation and interpreting requires intensive training in experimental design and data acquisition, pre-processing, and analysis. Translation scholars may also feel the need to seek cooperation with experts in neuroscience research. Since many experimental designs in cognitive neuroscience require strict experimental control, it is challenging

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for translation scholars to study life-like translation and interpreting processes by using neurophysiological or neuroimaging techniques (Hansen-Schirra 2017).

2.3 Translation Styles in CTIS Since the present study aims to investigate behavioral patterns during sight translation and to test whether translation behaviors correlate with professional experience, the behavioral–cognitive approach will be adopted to capture the cognitive processes via observations of the behavioral patterns of sight translators. Specifically, the present study is interested in investigating eye-movement behaviors in professional and novice sight translators during the preparatory reading of the source text for the subsequent oral production and as they read while speaking out the translation. With these aims in mind, the eye-tracking technique certainly seems to be the most appropriate method for the exploration of eye-movement patterns in sight translation. This brief review of major issues and findings using these four approaches to CTIS shows that, except for some research efforts adopting the psycholinguistic and behavioral approaches to the investigation of interpreters’ behaviors in spoken translation, few systematic attempts have been made to describe individual or shared characteristics of interpreting behaviors in sight translation. The present study builds on previous findings on problem triggers and fixation times by the identification and analysis of translation problems in sight translation from Chinese into English, and the triangulation of eye-movement data with interpreting output conducted to examine problem-solving behaviors. The present study extends previous work on interpreters’ behaviors in predominantly three aspects. First, the study investigates gaze behaviors in each stage of sight translation (i.e., preparation and actual sight translation) and examines correlations between gaze behaviors in preparation and gaze behaviors in actual production. Second, the study explores how interpreters coordinate between reading and speaking in actual sight translation by measuring the latency between the eyes and the voice (i.e., EVS). Compared with other eye measures, such as fixation durations, EVS has been underexplored—something this book hopes to remedy. Third, the study provides empirical evidence of the similarities and differences in behavioral styles of novice and professional interpreters in sight translation, from overall viewing and coordination behaviors to more specific problem-solving behaviors. In sum, the present study attempts to systematically explore translation styles by focusing on the two stages of sight translation, reading-speech coordination and translation problems, and, more importantly, the patterns of eye-movement behaviors associated with them among novice and professional interpreters during sight translation. To this end, the eye-tracking method will be used as the main research tool.

2.4 Summary

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2.4 Summary The cognitive process of translation and interpreting has been studied via the psycholinguistic, behavioral, corpus-based, and neurological approach. Most issues and findings within psycholinguistic and corpus-based approaches are concerned with strategic behaviors deployed in problem-solving processes, mainly operationalized by subjective verbalizations or offline product data, whereas the major topics and findings within the neurological approach are related to the cognitive control of simultaneous interpreters. Therefore, the investigation of objective, online behaviors in sight translation in the present study naturally falls within the behavioral approach. The brief review presented above regarding the major findings in the behavioral approach points toward the need for systematic examination of eye-movement behaviors in sight translation.

References Alves, F., & Albir, A. H. (2017). Evolution, challenges, and perspectives for research on cognitive aspects of translation. In J. W. Schwieter, & A. Ferreira (Eds.), The handbook of translation and cognition (pp. 537–554). West Sussex: Wiley-Blackwell. Alves, F., & Vale, D. C. (2011). On drafting and revision in translation: A corpus linguistics oriented analysis of translation process data. TC3: Translation: Computation, Corpora, Cognition, 1(1), 105–122. Angelone, E. (2010). Uncertainty, uncertainty management and metacognitive problem solving in the translation task. In G. M. Shreve & E. Angelone (Eds.), Translation and cognition (pp. 17–40). Amsterdam/Philadelphia: John Benjamins Publishing Company. Angelone, E. (2019). Process-oriented assessment of problems and errors in translation: Expanding horizons through screen recording. In E. Huertas-Barros, S. Vandepitte, & E. Iglesias-Fernandez (Eds.), Quality assurance and assessment practices in translation and interpreting (pp. 179–198). Hershey, PA: IGI Global. Araghian, R., Ghonsooly, B., & Ghanizadeh, A. (2018). Investigating problem-solving strategies of translation trainees with high and low levels of self-efficacy. Translation, Cognition & Behavior, 1(1), 74–97. https://doi.org/10.1075/tcb.00004.ara. Atari, O. (2005). Saudi students’ translation strategies in an undergraduate translator training program. Meta, 50(1), 180–193. https://doi.org/10.7202/010667ar. Baker, M. (1993). Corpus linguistics and translation studies: Implications and applications. In M. Baker, G. Francis, & E. Tognini-Bonelli (Eds.), Text and technology: In honour of John Sinclair (pp. 233–250). Amsterdam/Philadelphia: John Benjamins Publishing Company. Baker, M. (2000). Towards a methodology for investigating the style of a literary translator. Target, 12(2), 241–266. https://doi.org/10.1075/target.12.2.04bak. Bowles, M. A. (2010). The think-aloud controversy in second language research. London and New York: Routledge. Breedveld, H. (2002). Translation processes in time. Target, 14(2), 221–240. https://doi.org/10. 1075/target.14.2.03bre. Carl, M., & Báez, M. C. T. (2019). Machine translation errors and the translation process: A study across different languages. Journal of Specialised Translation, 31, 107–132.

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Carl, M., & Kay, M. (2011). Gazing and typing activities during translation: A comparative study of translation units of professional and student translators. Meta, 56(4), 952–975. https://doi.org/ 10.7202/1011262ar. Chmiel, A., Janikowski, P., & Lijewska, A. (2020). Multimodal processing in simultaneous interpreting with text: Interpreters focus more on the visual than the auditory modality. Target. https:// doi.org/10.1075/target.18157.chm. Chmiel, A., & Lijewska, A. (2019). Syntactic processing in sight translation by professional and trainee interpreters: Professionals are more time-efficient while trainees view the source text less. Target, 31(3), 378–397. Díaz-Galaz, S., Padilla, P., & Bajo, M. T. (2015). The role of advance preparation in simultaneous interpreting: A comparison of professional interpreters and interpreting students. Interpreting, 17(1), 1–25. Dragsted, B., & Carl, M. (2013). Towards a classification of translation styles based on eye-tracking and keylogging data. Journal of Writing Research, 5(1), 133–158. https://doi.org/10.17239/jowr2013.05.01.6. Elmer, S., & Kühnis, J. (2016). Functional connectivity in the left dorsal stream facilitates simultaneous language translation: An EEG study. Frontiers in human neuroscience, 10(60). https://doi. org/10.3389/fnhum.2016.00491. Englund Dimitrova, B., & Tiselius, E. (2014). Retrospection in interpreting and translation: Explaining the process? In R. Muñoz Martín (Ed.), Minding translation/Con la traducción en mente, Special issue of MonTI, 1(1), 177–200. Ericsson, K. A., & Simon, H. A. (1980). Verbal reports as data. Psychological Review, 87(3), 215–251. https://doi.org/10.1037/0033-295X.87.3.215. Even-Zohar, I. (2000). The position of translated literature within the literary polysystem. In L. Venuti (Ed.), The translation studies reader (pp. 192–197) (Original work published 1978). London and New York: Routledge. Feng, J. (2019). Analyzing translators’ attention allocation with translation progression graphs. Foreign Languages and Their Teaching (3), 85–97,146 [冯佳, 2019. 借助翻译进程图的译者注 意资源分配研究.《外语与外语教学》 (2013), 2085–2097, 2146]. García, A. M. (2019). The Neurocognition of translation and interpreting. Amsterdam/Philadelphia: John Benjamins Publishing Company. Halverson, S. (2003). The cognitive basis of translation universals. Target, 15(2), 197–241. https:// doi.org/10.1075/target.15.2.02hal. Hansen-Schirra, S. (2017). EEG and universal language processing in translation. In J. W. Schwieter, & A. Ferreira (Eds.), The handbook of translation and cognition (pp. 232–247). West Sussex: Wiley-Blackwell. He, Y. (2019). Translating and interpreting as bilingual processing: The theoretical framework. In D. Li, V. L. C. Lei, & Y. He (Eds.), Researching cognitive processes of translation (pp. 15–48). Singapore: Springer. Hervais-Adelman, A., Moser-Mercer, B., Michel, C. M., & Golestani, N. (2015). fMRI of simultaneous interpretation reveals the neural basis of extreme language control. Cerebral Cortex, 25(12), 4727–4739. https://doi.org/10.1093/cercor/bhu158. Heylen, K., Tummers, J., & Geeraerts, D. (2008). Methodological issues in corpus-based cognitive linguistics. In G. Kristensen & R. Dirven (Eds.), Cognitive sociolinguistics: Language variation, cultural models, social systems (pp. 91–127). Berlin: Mouton de Gruyter. Ho, C.-E. (2017). An integrated eye-tracking study into the cognitive process of English-Chinese sight translation: Impacts of training and experience. PhD diss.: National Taiwan Normal University. Huang, J. (2018). Working styles of student translators in self-revision, other-revision and postediting. In C. Walker, & M. Federico Federici (Eds.), Eye tracking and multidisciplinary studies on translation (pp. 145–184). Amsterdam/Philadelphia: John Benjamins Publishing Company.

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Hvelplund, K. T. (2019). Digital resources in the translation process–attention, cognitive effort and processing flow. Perspectives, 27(4), 510–524. https://doi.org/10.1080/0907676X.2019.157 5883. Ivanova, A. (2000). The use of retrospection in research on simultaneous interpreting. In S. Tirkkonen-Condit & R. Jääskeläinen (Eds.), Tapping and mapping the processes of translation and interpreting: Outlooks on empirical research (pp. 27–52). Amsterdam/Philadelphia: John Benjamins Publishing Company. Jakobsen, A. L. (2003). Effects of think aloud on translation speed, revision and segmentation. In F. Alves (Ed.), Triangulating translation: Perspectives in process oriented research (pp. 69–95). Amsterdam/Philadelphia: John Benjamins Publishing Company. Jakobsen, A. L. (2017). Translation process research. In J. W. Schwieter, & A. Ferreira (Eds.), The handbook of translation and cognition (pp. 21–49). West Sussex: Wiley-Blackwell. Jakobsen, A. L., & Schou, L. (1999). Translog documentation. In G. Hansen (Ed.), Probing the process in translation: Methods and results (pp. 151–186). Frederiksberg: Samfundslitteratur. Just, M. A., & Carpenter, P. A. (1980). A theory of reading: From eye fixations to comprehension. Psychological Review, 87(4), 329–354. Korpal, P. (2012). On language-pair specificity in sight translation: An eye-tracking study. In W. Baur, B. Eichner, S. Kalina, & F. Mayer (Eds.), Übersetzen in die zukunf (pp. 522–530). Berlin: BDÜ Fachverlag. Korpal, P., & Stachowiak-Szymczak, K. (2018). The whole picture: Processing of numbers and their context in simultaneous interpreting. Poznan Studies in Contemporary Linguistics, 54(3), 335–354. https://doi.org/10.1515/psicl-2018-0013. Korpal, P., & Stachowiak-Szymczak, K. (2020). Combined problem triggers in simultaneous interpreting: Exploring the effect of delivery rate on processing and rendering numbers. Perspectives, 28(1), 126–143. Krings, H. P. (1986). Translation problems and translation strategies of advanced German learners of French (L2). In J. House & S. Blum-Kulka (Eds.), Interlingual and intercultural communication: Discourse and cognition in translation and second language acquisition studies (pp. 263–276). Tübingen: Gunter Narr Verlag. Künzli, A. (2009). Think-aloud protocols–A useful tool for investigating the linguistic aspect of translation. Meta, 54(2), 326–341. https://doi.org/10.7202/037684ar. Lang, Y, Hou, L., & He, Y. (2019). The effect of multimodal input on the interplay of cognitive processing routes in simultaneous interpreting: A corpus-assisted cognitive study. Journal of Foreign Languages, 49(2), 75–86 [朗月, 侯林平, 何元建. 2019. 多模态输入对同传认知加工 路径影响的库助认知研究.《外国语》2049 (2012), 2075–2086]. Lee, J. (2012). What skills do student interpreters need to learn in sight translation training? Meta, 57(3), 694–714. https://doi.org/10.7202/1017087ar. Li, D. (2017). Development and methodology of cognitive translation and interpreting studies. Foreign Languages in China, 14(4), 1+11–13 [李德凤. 2017. 翻译认知过程研究之沿革与方 法述要.《中国外语》 2014 (2014), 2011+2011–2013]. https://doi.org/10.13564/j.cnki.issn.16729382.2017.04.001. Li, D., Lei, V. L. C., & He, Y. (2019). Researching cognitive processes of translation. Singapore: Springer. Li, D., Zhang, C., & Liu, K. (2011). Translation style and ideology: A corpus-assisted analysis of two English translations of Hongloumeng. Literary and linguistic computing, 26(2), 153–166. https://doi.org/10.1093/llc/fqr001. Liu, M., Schallert, D. L., & Carroll, P. J. (2004). Working memory and expertise in simultaneous interpreting. Interpreting, 6(1), 19–42. https://doi.org/10.1075/intp.6.1.04liu. Lörscher, W. (1991). Translation performance, translation process, and translation strategies: A psycholinguistic investigation. Tübingen: Gunter Narr Verlag. Lu, S., Carl, M., Yao, X., & Wenchao, S. (2020). Predicting translation behaviors by using Hidden Markov Model. Translation, Cognition & Behavior, 3(1), 76–99.

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Ma, X. (2019). Effect of word order asymmetry on cognitive process of English-Chinese sight translation by interpreting trainees: Evidence from eye-tracking. PhD diss.: The Hong Kong Polytechnic University. Munday, J. (2001). Introducing translation studies: Theories and applications. London and New York: Routledge. Nida, E. A., & Taber, C. R. (1969). The theory and practice of translation. Leiden: E. J. Brill. Płu˙zyczka, M. (2013). Eye-tracking supported research into sight translation: Lapsological conclusions. In S. Grucza, M. Plu˙zyczka, & J. Zajac (Eds.), Translation studies and eye-tracking analysis (pp. 105–138). Frankfurt am Main, DEU: Peter Lang AG. Rinne, J. O., Tommola, J., Laine, M., Krause, B. J., Schmidt, D., Kaasinen, V., et al. (2000). The translating brain: Cerebral activation patterns during simultaneous interpreting. Neuroscience Letters, 294(2), 85–88. https://doi.org/10.1016/S0304-3940(00)01540-8. Rodríguez-Inés, P. (2017). Corpus-based insights into cognition. In J. W. Schwieter, & A. Ferreira (Eds.), The handbook of translation and cognition (pp. 265–289). West Sussex: Wiley-Blackwell. Rojo, A., & Valenzuela, J. (2013). Constructing meaning in translation: The role of constructions in translation problems. In A. Rojo & I. Ibarretxe-Antuñano (Eds.), Cognitive linguistics and translation: Advances in some theoretical models and applications (pp. 283–310). Berlin: De Gruyter Mouton. Schaeffer, M., Nitzke, J., Tardel, A., Oster, K., Gutermuth, S., & Hansen-Schirra, S. (2019). Eyetracking revision processes of translation students and professional translators. Perspectives, 1–15. https://doi.org/10.1080/0907676x.2019.1597138. Seeber, K. G. (2017). Multimodal processing in simultaneous interpreting. In J. W. Schwieter, A. Ferreira (Eds.), The Handbook of Translation and Cognition (pp. 461–475). West Sussex: Wiley-Blackwell. Stachowiak-Szymczak, K. (2019). Eye movements and gestures in simultaneous and consecutive interpreting. New York: Springer. Stachowiak-Szymczak, K., & Korpal, P. (2019). Interpreting accuracy and visual processing of numbers in professional and student interpreters: An eye-tracking study. Across Languages and Cultures, 20(2), 235–251. Su, W., & Li, D. (2019). Identifying translation problems in English-Chinese sight translation: An eye-tracking experiment. Translation and Interpreting Studies, 14(1), 110–134. https://doi.org/ 10.1075/tis.00033.su. Tiselius, E., & Jenset, G. B. (2011). Process and product in simultaneous interpreting: What they tell us about experience and expertise. In C. Alvstad, A. Hild, & E. Tiselius (Eds.), Methods and strategies of process research: Integrative approaches in translation studies (pp. 269–300). Amsterdam/Philadelphia: John Benjamins Publishing Company. Tommola, J., Laine, M., Sunnari, M., & Rinne, J. O. (2000). Images of shadowing and interpreting. Interpreting, 5(2), 147–167. https://doi.org/10.1075/intp.5.2.06tom. Toury, G. (2000). The nature and role of norms in translation. In L. Venuti (Ed.), The translation studies reader (pp. 198–211). (Original work published 1978). London and New York: Routledge. Wang, W., & Li, D. (2015). How student and professional interpreters in Chinese-English consecutive interpreting differ in their choice of interpreting strategies. Chinese Translators Journal (6), 41–47, 129 [王巍巍, 李德超. 2015. 汉英交替传译策略使用特征—基于有声思维法的学 生译员与职业译员对比研究.《中国翻译》(6), 41–47, 129].

Chapter 3

Translation Style in Sight Translation

Abstract This chapter reviews the existing literature on behavioral styles in translation and interpreting. First, the concept of translation styles in the present study is presented in Sect. 3.1, followed by the descriptions of the features of sight translation in Sect. 3.2. Section 3.3 considers behavioral styles in a global level, from the perspectives of translation stages, interdependency of behaviors, and coordination between comprehension and production. Section 3.4 continues the review on previous studies related to behavioral styles at a local level, from the aspects of problem identification behaviors, problem-solving behaviors, and the influence of problems on coordination behaviors. The chapter closes in Sect. 3.5 with a review on studies of behavioral patterns between novice and professional interpreters and translators in Sect. 3.5. Keywords Translation stages · Interdependency of behaviors · Coordination between comprehension and production · Problem identification · Problem-solving

3.1 Concept of Translation Style In stylistic approaches to translation studies, style is defined as an expression of choices and attitudes of the source text author and the target text translator, as well as its effects on the readers (Boase-Beier 2014). In systemic functional linguistics, style is linked to the concept of register, which means linguistic variations of the text based on the topic, the participants involved, and how linguistic resources are organized in a certain situation or context (Halliday and Matthiessen 2014). In corpus-based translation studies, translation style, or style of the translated text, refers to the linguistic features of the target text. Translation style is the combination of the styles of the source text author and the translator, and presumably the style of the editor (Saldanha 2011). On the other hand, translator style focuses on the linguistic features of the translator (Baker 2000; Li 2017). Similar to translation style in corpusbased translation studies, interpreting style is concerned with the linguistic features of the interpreting output (Kajzer-Wietrzny 2013). Although interpreting style was sometimes viewed as the method of interpreting, using indicators such as pauses and © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2020 W. Su, Eye-Tracking Processes and Styles in Sight Translation, New Frontiers in Translation Studies, https://doi.org/10.1007/978-981-15-5675-3_3

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time lags (Yagi 2000; Van Besien and Meuleman 2008), interpreting style in this sense is more similar to strategies than style, per se (Baxter 2019). Therefore, it could be seen that the concept of style in studies that use stylistics, systemic functional linguistics, and corpus to explore translation and interpreting is primarily based on linguistics. In the present study, translation style is not concerned with linguistic features, but rather with behavioral characteristics and patterns. Dragsted and Carl (2013) define it as the features and characteristics of translation behaviors. Other researchers have used different terms for it, including translator profile (Alves and Vale 2011), process profile (Englund Dimitrova 2005), prototypical behavior (Mesa-Lao 2014), working patterns (Timarová et al. 2011), behavioral patterns (Schaeffer et al. 2016; MartínezGómez et al. 2018; Nitzke 2019), cognitive rhythm (Whyatt et al. 2016), translator style (Pym 2009), working style (Jakobsen 2002; Huang 2018), production style (Asadi and Séguinot 2005), behavioral style (Jakobsen 2017), among others. Translation style could be a translator’s individual behavioral features when performing a translation task, which remain more or less unchanged throughout their work (Englund Dimitrova 2005). Translation style in this sense resembles a translator’s habits when performing translation tasks (Antunovi´c and Pavlovi´c 2011). Translation style could also be defined as individual behavioral characteristics which vary from task to task and from written translation to oral interpreting. According to Englund Dimitrova (2005), it is this definition which is more likely to be accurate. The translation behaviors of each translator or interpreter may be further categorized into different groups based on their shared features, and different translator or interpreter groups may share common behavioral characteristics (Dragsted and Carl 2013). In the present study, translation styles are defined as features and characteristics of eye-movement behaviors in sight translation. Furthermore, translation styles refer to the individual or group characteristics of translation behaviors, or behavioral patterns shared by different groups.

3.2 Sight Translation Sight translation refers to “the oral rendition of a written document in the target language” (Mellinger 2017, p. 312). Sight translation is also known to as sight interpreting, but this term usually refers to SI with text. In the present study, interpreters produce oral interpretations of the written text without the presence of the source text speaker, and therefore the term sight translation is used in the study. Sight translation is a particularly interesting modality due to its use of two distinct modes, the written and the verbal, and it is thus considered “a hybrid between written translation and interpreting” (Dragsted et al. 2009, p. 589). Sight translation has the same written input mode as written translation, but the two differ greatly in terms of the output mode. Written translation is a recursive, repetitive process where translators can revise the target text at different points of time until they are satisfied with the output, while sight translation is a one-go process where only a single chance

3.2 Sight Translation

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of producing a satisfying interpretation exists. Therefore, there is no separate revision phase in sight translation, and revisions, if any, occur as sight translators interpret the text. Furthermore, written translators do not need to produce translations concurrently as they are able to read the source text in their own time, whereas sight translators are required to read the source text and speak out the translations simultaneously. Dragsted et al. (2009) investigated how the oral mode of sight translation affected eye movements during reading. They designed an eye-tracking experiment where four professional interpreters performed a sight translation task, while four professional translators performed both a sight and written translation task. They found that translators tended to look at different directions with shorter fixation durations on the source text in the written mode, while interpreters focused almost exclusively on the source text (with slightly longer fixation durations) and read linearly during sight translation. The findings show that interpreters tend to concentrate on reading the source text in sight translation, while translators divide their attention between the source and target texts. Later studies have further suggested that written translators allocate more cognitive resources for target text processing than for source text processing (Hvelplund 2017). The vast difference in the output mode could explain why the same written input mode exerts different effects on these two types of translation. Shreve et al. (2010) designed an eye-tracking experiment to compare sight translation with written translation so as to gain deeper insights into the side effects of the visual input of the written texts. They investigated the effect of syntactic complexity of the ST on the eye movements of translation students in sight translation, and the syntactic effect on the production parameters in written translation. The results showed an increased total reading time, number of fixations, and regressions when students sight translated the complex segment in the first of the two experimental texts. This syntactic complexity effect, however, was not found in written translation. The findings indicated that the visual presence of source texts had a greater impact on sight translation than on written translation, because, as mentioned above, written translators have the flexibility to distribute their attention between the source and target texts, whereas sight translators must fixate on the source text (although they are able to look away from it), thereby increasing the risk of visual interference. In terms of simultaneity of comprehension and production, sight translation is more akin to SI than written translation. As Pöchhacker aptly states, sight translation is “a special type of simultaneous interpreting” (2016, p. 20). What makes sight translation special is that the source text is constantly available during the process, so sight translators do not have the added worry of potentially losing chunks of information due to temporary working memory saturation, as is the case in SI (Gile 2009). Lambert (2004) reported that translation students attained much higher performance scores in sight translation and in SI with text than in SI, suggesting that the visual input of written texts may improve performance, along with its possible side effect of interference (as mentioned above). Furthermore, because of the visual input, sight translators can produce interpretations according to their own pace of working, while simultaneous interpreters have no option but to adjust themselves to the speaker’s speed.

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Viezzi (1989) compared the information retention rate of the source texts after interpreting students and professional interpreters performed four tasks: listening, reading aloud, SI, and sight translation with English and French as the source languages, and Italian as the target. Information retention was tested via interpreters’ recall or memory of the text content. He found that for all participants, less information was retained after sight translation than after SI, especially when the language pair was English and Italian—the pair with the fewest similarities. The poorer memory for the text in sight translation than in SI might be attributed to the fact that interpreters in sight translation can consult the text whenever necessary, so they may feel that they do not need to exert as much effort to remember the text in sight translation as in SI (Lee 2012). Consequently, they perform the so-called shallow scans (Shreve et al. 2010, p. 65) of the source language as reflected by increased regressive eye movements in reading in sight translation. In a professional sphere, two forms of sight translation are common: unrehearsed sight translation and rehearsed or prepared sight translation (Lambert 2004; Sandrelli 2003; Song 2010; De Laet 2012). The most significant difference between these two types of sight translation lies in whether sight translators are given the opportunity to read the text prior to actual sight translation. In unrehearsed sight translation, sight translators start interpreting upon receiving the text. In rehearsed sight translation, sight translators can read the text, consult dictionaries, and take notes before actual sight translation begins. Therefore, rehearsed sight translation can be subdivided into two stages: reading in preparation for sight translation and proper sight translation (or actual sight translation). The preparation stage involves source text reading, while the stage of actual sight translation involves concurrent source text reading and speaking, provided that only the source text is available for sight translation. The preparation stage, Stage 1, is the period of time when sight translators read the text prior to actual sight translation. Whether or not the preparation stage exists depends on the form of sight translation utilized. The present study includes the preparation stage as sight translators are typically allowed to read the text in advance. In Stage 1, the dominant activity is source text reading, which is aimed at comprehending the source text and possibly producing some tentative translations in the mind before the actual process begins. The stage of actual sight translation, Stage 2, refers to the period of time when sight translators actually translate the text. Stage 2 comprises two phases: the orientation phase and the rendition phrase (cf. Jakobsen 2002). The orientation phase starts from the moment the sight translator has read the source text until they utter the first word. The function of source text reading in the orientation phase is to position one’s eyes to the first sentence and have a brief glance at the first words that are about to be interpreted, so as to accustom the translator to the text. The rendition phase starts from the first interpretations of the source text until the sight translator completes the interpretation. Two types of reading, source text reading only and source text reading while speaking, occur in this phase. It is expected that participants engage themselves mostly in concurrent reading and speaking due to the time pressure of sight translation.

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It is assumed that the orientation phase will not be time consuming and thus could be merged with the rendition phase. This is due to sight translators in the rehearsed form of sight translation having read the text in advance. The reason why the orientation phase is treated separately is that the separation of the orientation and rendition phase makes it easier to compare sight translation to the existing literature in written translation from the behavioral–cognitive perspective. However, this book combines the two phases in the analysis of translation style. To sum up, viewing the entire process of rehearsed sight translation as two stages will be the basis for operationalizing processing style during sight translation. This study operationalizes behavioral style in sight translation in terms of global and local styles. As mentioned in Chap. 1, global styles are reflected by eyemovement patterns at the more general textual level, whereas local styles focus on eye-movement patterns at the more specific lexical level, i.e., at a specific problem word.

3.3 Global Behavioral Styles Global behavioral styles focus on how interpreters in sight translation process the entire text. The operationalization of behavioral styles in sight translation is mainly inspired from studies in written translation. Previous studies on written translation styles provided several parameters for the investigation of global behavioral patterns in written translation, but I will adopt the most relevant parameters to the features of sight translation. This section reviews translators’ and interpreters’ behaviors in terms of different translation and interpreting stages, interaction between behaviors in different stages, and coordination behaviors between comprehension and production.

3.3.1 Behaviors in Different Stages In the behavioral approach to CTIS, translation style has been studied according to behavioral patterns in the three phases of written translation, i.e., orientation, drafting, and revision. A reason for this could be that to consider translation as one whole process may not accurately reflect different behavioral profiles. Jakobsen (2003) compared the overall text production speed of translation of students and professional translators when performing written translation with and without thinking aloud. He found that in both conditions, professionals translated faster than students, but the difference was not as pronounced as expected. Jakobsen argued that the overall translation speed which was calculated across the whole task “may have skewed the difference between the two groups” (2003, p. 77). Professionals might spend much longer than students in certain periods of the translation process while investing much less time than students in other periods

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of the process. If the translation task was considered to be an entire process, the differences between the two groups could seem smaller than they actually were. When he identified three phases, namely orientation, drafting, and revision in the process of written translation, professionals were found to work much faster than students in the drafting phase, but took longer than students in the revision phase. Similarly, Wang and Xu (2015) compared the total task time of novice translators and semiprofessional translators in written translation of a different language pair— Chinese and English—but only found a slight difference between the two groups. When the authors looked more closely at their time allocation to different phases, they found that semiprofessionals spent less time than novices drafting the translation, but invested more time than novices in orientation. In her TA study of written translation, Breedveld (2002) noticed that translators usually read through the text several times during the entire translation process but spent different amounts of time on each read, and performed different amounts of activities, such as source text reading, target text reading, and writing in each runthrough of the text. She concluded that each stage of the translation process was dominated by different translation activities which had different functions as the translation process proceeded. This finding serves as a reminder that translation behaviors might vary according to the moment they actually occur, and it is important to describe behavioral patterns based on the different stages of the translation process. I acknowledge that the different phases in written translation do not directly correspond to the different stages in prepared sight translation. For instance, orientation in written translation naturally occurs throughout the entire process of written translation, whereas advance preparation in sight translation must be explicitly instructed and does not even exist in the (more stressful) form of sight translation. Another example is the time available to written translators to revise their output at the end of the revision phase, while a separate revision phase would be highly unlikely in the mode of sight translation due to its inherent time pressure. Consequently, the categorizations of written translation styles, mostly operationalized by time distribution and revision behaviors, such as “correctional planners” (Englund Dimitrova 2005, p. 152), “on-screen thinkers” (Asadi and Séguinot 2005, p. 528), “online revisers” (Dragsted and Carl 2013, p. 148), and “drafter” (Alves and Vale 2011, p. 115), provided little clarity on the behavioral patterns used in the mode of sight translation. However, the idea that different stages of the translation process might lead to different translation behaviors—and that different translators might exhibit different behaviors in different phases of the process—has shed light on the investigation of behavioral styles in sight translation. Indeed, in prepared sight translation, interpreters have been advised to employ different strategies in prior preparation and in actual sight translation (Gile 2009), suggesting that interpreters could indeed demonstrate different behaviors in each stage. Therefore, the first step of the present study is to examine and compare interpreters’ overall behaviors in prior preparation and the following actual sight translation by adopting parameters used in studying written translation behaviors, such as time allocation across different stages, and eye-movement measures such as fixation durations.

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Preparation is a common practice prior to actual interpreting (Gile 2009; Kalina 2015; Kader and Seubert 2015). It has been applied in interpreting studies to simulate working scenarios (Ruiz Rosendo and Galván 2019) and constitutes one of the research foci in empirical interpreting studies (Pérez-Pérez 2018; Xu 2018). Preparation prior to actual sight translation has also been observed in several studies (see Table 3.1). Although preparation in these studies was similar to what Gile (2009) called “last-minute preparation” (p. 145), it differed between studies mainly in two aspects: how much time was allowed for pre-reading, and what materials were provided for participants. As shown in Table 3.1, most studies specified the time limit for advance preparation and provided participants with the same source text that was about to be interpreted in the subsequent actual sight translation. The present experiment will provide the same source text to be interpreted in actual sight translation for participants in prior preparation. The preparation time is to be no more than 15 min for each source text. Few studies have investigated how different stages of the translation and interpreting process influence time allocation and eye-movement behaviors. Dragsted’s Table 3.1 Preparation time and materials in the research of prepared sight translation Study

Preparation time

Preparation materials (word length)

Agrifoglio (2004)

Less than five minutes

The same source text that was to be sight translated (800 words)

Lambert (2004)

Approximately ten minutes The same source text that was to be sight translated (300 words)

Lee (2012)

Six minutes

The same source text that was to be sight translated (600 words)

Chmiel and Mazur (2013) Ten seconds

The first page of the same source text that was to be sight translated (unknown)

Zheng and Xiang (2014)

Ten minutes

A passage providing background information for the source text that was going to be sight translated (559 words)

Ho (2017)

A few minutes

Some technical words, their definitions, and interpretations (unknown)

Zheng and Zhou (2018)

Three minutes

The same source text that was to be sight translated (unknown) and relevant glossary (unknown)

Ma (2019)

Unknown

Background information of the source text that was about to be sight translated, and relevant glossary with corresponding translations (unknown)

Su and Li (2019)

Self-paced

The same source text that was to be sight translated (around 50 words)

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(2010) study may shed some light on this influence. Although the mode she studied was written translation, there may well be implications for sight translation. She investigated the reading patterns of students and professional translators in reading for the subsequent actual written translation and reading during the actual written translation. Participants were explicitly instructed to pre-read the source text for the upcoming actual written translation—an instruction similar to that used in the present study. Dragsted (2010) found that each translator group spent more time in actual translation than in advance preparation. One explanation for this could be that actual written translation generally does not require concurrent reading and typing, and therefore some planning activities in prior preparation could be performed in actual written translation. Each group exhibited a slightly longer fixation duration on the target text in actual translation than on the source text in preparation, possibly because reading the target text in actual translation involved not only comprehension but also reformulation processes (Hvelplund 2017). The results of Dragsted’s (2010) study showed that time distribution and eye-movement behaviors were affected by different stages of the translation process due to the different demands they posed to the translators. To recap, the investigation of behavioral patterns in different stages of the translation and interpreting process is crucial for capturing the variability of translators’ and interpreters’ behaviors, and thus the variability of their cognitive activities during the entire process of translation and interpreting (Breedveld 2002). Therefore, as the first step of the present study, I will investigate how participants allocate time and demonstrate eye-movement behaviors in preparation and actual sight translation, and whether the allocation of time and the patterns of gaze behaviors depend on interpreting experience.

3.3.2 Interaction Between Behaviors The previous section argued that translators and interpreters might respond to different task requirements in different stages of the process, as reflected by their different behavioral patterns. Apart from the variation in translation and interpreting processes, it is also important to stress the interdependency or correlations between behaviors that occur prior to or after the start of the process, either within the same phase or between different stages. As Breedveld (2002) pointed out: Translators do not do the same thing all the time but do at any moment what (they believe) is needed at that moment given the state of the text-in-production, and also given everything that they have done before. This implies that activities are not performed at random, but in cohesion with one another, and that there must be a strong functional dependency between activities. (p. 231)

Several studies concerning the interaction between behaviors in written translation within the behavioral approach were examined in preparation for the current research—the study of Dragsted and Carl (2013) being perhaps the most relevant.

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They investigated the behavioral styles of students and professional translators when performing written translations from English into Danish, using eye-tracking and key logging techniques as their research methods. They divided the entire translation process into three stages: planning, drafting, and revising, and then examined the reading and typing behaviors largely through translation progression graphs in each of the three phases to see how behaviors in the preceding phase correlated with behaviors in the subsequent phase. They found that translators who read only a handful of words in the initial planning phase tended to read a small context and revise the text as they drafted the translation. Alternatively, translators who pre-read a higher percentage of the text in the planning phase tended to read a larger context in drafting and make their revisions only when the first draft was finished. They concluded that translators exhibited consistent behaviors across the three phases: translators who focused their attention more locally in the initial stage continued to be more locally oriented in the following phases, and translators who focused their attention more globally in the beginning continued this global orientation in later phases. In spoken translation, previous studies have largely focused on how the inclusion of prior preparation affects interpreting performance (Lee 2012; Xu 2018; Pérez-Pérez 2018), and researchers began to examine how prior preparation affects the subsequent actual interpreting. Some studies revealed that advance preparation accelerated the interpreting process. For example, Zheng and Xiang (2014) studied the effect of cultural background knowledge among undergraduate students when processing metaphors in sight translation from English into Chinese. They found that the group provided with background information prior to actual sight translation spent significantly less time processing metaphors than the group which received no background information. The smaller amount of processing time on metaphors was interpreted as less cognitive load experienced by participants when processing metaphors in actual sight translation. They concluded that prior preparation of textrelevant knowledge reduced the cognitive load of processing metaphors in actual sight translation. Another example was Díaz-Galaz et al. (2015), who investigated whether the prior preparation of topic-related materials facilitated the process of SI from English into Spanish performed by students and professional interpreters. The process of SI was operationalized by the latency between the ear-voice spans. Advance preparation led to shorter ear-voice span, and the positive effect of prior preparation did not differ depending on the interpreters’ levels of experience. Since shorter ear-voice span reflected more fluent and speedy processing, the findings showed the facilitating effect of advance preparation in the process of actual interpreting. However, Macizo and Bajo (2009) reported the opposite findings. They examined the effect of reading a prior summary on the reading times of actual sight translation and compared it with the prior reading effect on the reading times of reading aloud. The presence of a summary prior to actual sight translation slowed down the process of actual sight translation. However, this negative effect reversed into a positive effect when it came to reading aloud. They concluded that it was harder for translators to make full use of prior knowledge in a more cognitively effortful task such as sight translation.

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Taken together, previous studies do not provide consistent results regarding the role of advance preparation in actual interpreting. Therefore, I would like to examine how preparation styles affect the process of actual sight translation, and whether the effect depends on the professional experience of the interpreter. However, there are three things in need of clarification. First, all the participants in the current study are allowed to pre-read the source text in advance. Thus, unlike the previous studies of Zheng and Xiang (2014), Díaz-Galaz et al. (2015), and Macizo and Bajo (2009) mentioned above, the current study examines whether interpreters display similar or dissimilar trends in their gaze behaviors across prior preparation and actual sight translation, for example, whether the time of actual sight translation increases or decreases as preparation time increases, or whether the fixation duration displayed in actual sight translation increases or decreases as fixation duration exhibited in prior preparation increases. Secondly, the preparation materials in the present study are to be selected from real-world speeches and will be the same texts to be sight translated in the subsequent actual sight translation. Since speech scripts are frequently received by professional interpreters as preparation materials in interpreting practice (Han 2015), these materials simulate real-life interpreting practice, which could strengthen the implications of the results. Thirdly, actual sight translation will begin immediately after participants finish pre-reading the source text.

3.3.3 Coordination Behaviors The last aspect of global translation styles to be discussed concerns how interpreters coordinate reading and speaking in actual sight translation. Coordination between comprehension and production is an essential dimension of translation style due to interlingual production being a key process in translation and interpreting tasks. The issue of coordination, especially in SI, has been studied for several decades by means of ear-voice span (Goldman-Eisler 1972; Barik 1973; Lee 2002; Timarová et al. 2014; Defrancq 2015; Chmiel et al. 2017). By contrast, the investigation of coordination behaviors in written and sight translation has just started to attract research attention following the development of keystroke logging and eye-tracking. Dragsted’s (2010) study was believed to be the first to systematically examine behavioral patterns of coordination in written translation. The key indicator of coordination behaviors was the eye-key span (EKS), which referred to the time lag between the reading of the input word and the typing of its translation (Dragsted and Hansen 2008). Since the source text in written translation is always presented for translators, one source text word could be read several times and thus receive more than one fixation. Considering this, Dragsted (2010) further distinguished two types of EKS, namely EKS from the first fixation of the input word to the moment its corresponding output word was typed, and EKS from the last fixation of the input word to the typing of its translation.

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In sight translation, coordination behaviors could be described by the eye-voice span (EVS). Following oral reading research, the EVS could be measured as the distance in time, letters, or words (Laubrock and Kliegl 2015). In the present study, the EVS is measured in temporal units because it “allows better comparability of findings across studies” (Timarová et al. 2011, p. 123). Thus, the EVS in sight translation can be defined as the time span between the beginning of the fixation on a source text word and the beginning of the articulation of its translation. The EVS in sight translation in oral reading research is also known as the fixation-speech interval (Inhoff et al. 2011) and the eye-voice lead (De Luca et al. 2013). In the present study, the global coordination style is measured by the EVS at the textual level, namely the average value of the EVS of each word in each text. Like written translators, sight translators are able to refer to the source text repeatedly, so it is reasonable to assume that a source text word might attract more than one fixation. Thus, following Dragsted’s (2010) classification of EKS from first fixation and EKS from last fixation, I distinguish two types of EVS: maximal EVS (Max. EVS) and minimal EVS (Min. EVS). Max. EVS is defined as the time span from the onset of the first fixation on a source text word to the onset of its oral rendition, whereas Min. EVS will be used to refer to the time interval from the onset of the last fixation on a source text word to the onset of its oral rendition. Due to there being few studies involving coordination and time lag in sight translation, it might be pertinent to review relevant studies in other modes of translation. Before doing so, however, it is necessary to clarify the different types of time lag measures used in different modes of translation. Max. EVS in sight translation is comparable to ear-voice span in SI and EKS from first fixation in written translation. All these measures are calculated from the onset time of the first reception of the source text either by the ears or the eyes. Since it is not possible in SI to repeatedly listen to the speech, there can be no such thing as minimal ear-voice span. However, in written translation and sight translation, a source text word could be read more than one time before its translation is produced. Therefore, Min. EVS in sight translation can be considered comparable to EKS from the last fixation in written translation. Maximal time lag has been considered closely related to delivery fluency. In SI, “short EVS indicates that the processing was smooth and speedy” (Lee 2002, p. 601). In written translation, shorter EKS from first fixation could reflect faster coordination between reading and typing, whereas longer EKS from first fixation could be indicative of a slower reading-typing coordination (Jakobsen 2017). In this scenario, the translator group with shorter EKS from first fixation on average produced more fluent output and had a shorter total production time compared to the translator group with longer EKS from first fixation on average (Dragsted 2010). To further complicate the description of coordination styles, integrated coordination has been used to describe a coordination pattern where translators display relatively fast coordination from first fixation and relatively short EKS from last fixation. Sequential coordination has been used to define a converse coordination style (Dragsted 2010; Jakobsen 2017). In general, “time lag could serve as a temporal variable reflecting processing speed, providing an opportunity to further probe the underlying cognitive processes”

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(Timarová et al. 2011, p. 145). When comparing the maximal time lag of two translator or interpreter groups, it is important to also compare their total production time and decide whether maximal time lag, such as Max. EVS in sight translation, could indeed reflect the speed of coordination behaviors. The reason for this is that maximal time lag could also reflect more than just the temporal aspect of coordination between comprehension and production. Maximal time lag could also reflect “to what extent translators read ahead of the word under production” (Timarová et al. 2011, p. 132). For instance, a relatively long Max. EVS in sight translation does not necessarily indicate that reading-speech coordination has slowed down. Rather, it could reflect a coordination style where an interpreter read a relatively large context without sacrificing fluency of delivery (Dragsted et al. 2009). In this scenario, interpreters systematically read further ahead of the word to be sight translated as they utter the translation of the previous text. Therefore, the identification of coordination styles, as reflected by Max. EVS in sight translation, should take output disfluencies and total production time into account. It is also apposite to inspect the synchronized eye movements and oral renditions to probe into the reading behaviors and speech activities during coordination. Minimal time lag reflects how closely in time a translator or interpreter fixates on a particular word right before its translation is produced. It is considerably shorter than the maximal time lag, and a very short minimal time lag of word N could indicate that the translators or interpreters remain fixated on word N as they deliver its translation. As the minimal time span of a word increases, the probability that the eyes fixate on words other than word N immediately before its oral rendition increases. As Dragsted (2010) observed, professionals’ much shorter EKS from last fixation than students’ reflected that “the fixation on the ST word most often occurs immediately before production, i.e., no other fixations occur between the last fixation and production” (p. 52), whereas students’ longer EKS from last fixation than professionals’ reflected that students might have “several fixations on words other than the ST unit to be translated in between the last fixation on the ST word and the production of its equivalent” (p. 52). The conjecture of the link between the gaze behaviors and the minimal time lag should be further justified with the visual inspection of synchronized scanpaths and oral production. The minimal time lag, such as the EKS from last fixation in written translation, has been interpreted as “the immediate effort of switching from the reading mode to the writing mode” (Dragsted 2010, p. 51). The minimal time span in actual sight translation, namely the Min. EVS, could also be indicative of the preference for refreshing working memory (Arnt Lykke Jakobsen, personal communication, July 23, 2018). In fact, studies in oral reading have found that a larger EVS led to a higher probability of making regressive saccades (Inhoff et al. 2011; Laubrock and Kliegl 2015), indicating that larger EVS increased memory load and possibly deactivated the information already read, meaning that the eyes would have to go back to keep closer to the voice so as to maintain a manageable working memory and allow for the reactivation of the information to be uttered (Holmqvist et al. 2011). Therefore, reading-speech coordination behaviors as reflected by Min. EVS in sight translation could indicate the need for updating working memory.

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3.4 Local Behavioral Styles In the previous sections, I have reviewed the existing literature on behavioral styles in translation and interpreting, with an emphasis on behavioral patterns at a global, textual level. In this section, I shall take a closer look at the behavioral patterns at a local, lexical level, and review relevant studies on problem identification and problem-solving behaviors. Furthermore, I will review previous studies on the coordination of comprehension and production, with an emphasis on its relationship with translation problem triggers.

3.4.1 Problem Identification Behaviors Translation problems have been one of the research foci in translation and interpreting studies. Krings (1986) argued that previous studies of translation problems “have tried either (…) to predict translation problems prospectively on the basis of a linguistic account of the source-language text or (…) to identify translation problems retrospectively by an error analysis of the target-language text the subjects produced” (p. 266). He claimed that neither predicted problems based on a linguistic analysis of the source text nor problems based on an error analysis of translation products are fully representative of the problems that actually occur throughout the translation process. He thus emphasized the need to investigate translation problems from the perspective of the translation process itself. Indeed, it is vital to bear in mind that translation problems should not be confused with translation errors, as Angelone (2018) argued that “problems and errors are not one and the same” (p. 31). Translation problems are manifested in the process, while translation errors are manifested in the product. The pioneering work of Krings (1986) and Lörscher (1991), who used TAPs to document problems in the translation process, has encouraged research on translation problems from the process perspective. Translation problems have been identified in different phases of the translation process using various methods. Problems were identified in the initial preparation stages by using translators’ or interpreters’ markup of the source text as problem indicators (Lee 2012; Gile 2009; Akbari 2017; Angelone 2018). Problems have also been detected in the progression of actual translation or interpreting processes by means of concurrent TAPs (Künzli 2009), concordance search logs (Valli 2014), screen recording (Angelone 2018, 2019), key logging, and eye-tracking (Płu˙zyczka 2013; Su and Li 2019; Nitzke 2019; Muñoz Martín and Cardona Guerra 2019). Finally, problems occurring in actual translation or interpreting processes could be identified immediately after the completion of the translation or interpreting task using retrospective protocols (Tiselius and Jenset 2011; Englund Dimitrova and Tiselius 2014; Shamy and de Pedro Ricoy 2017; Ferreira et al. 2018) and questionnaires (PACTE 2011; Arumí Ribas 2012).

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Problems identified in prior preparation include words and expressions that might cause difficulties in the subsequent actual translation or interpreting, and thus are termed anticipated or potential problems, whereas problems identified in the process of actual translation and interpreting are usually called actual problems (Angelone 2018). For spoken translation such as SI and sight translation, immediate retrospection is one of the few methods to detect translation problems that arise during the actual interpreting itself. Englund Dimitrova and Tiselius (2014) examined the reliability and completeness of retrospective protocols immediately after SI and written translation from English into Swedish performed by translation and interpreting students and professionals. Regarding the reliability of retrospection, only a few who reported problems in retrospection did not have problem indicators in the translation and interpreting process, the main reason for which might be that the definition of process indicators was too strict to reflect all possible problems. However, in terms of the completeness of retrospection, most problem indicators in the process were not mentioned in the reported problems, leading the authors to conclude that the reported problems “can only explain a limited number of the potential problems in the process” (ibid, pp. 177–178). Translation problems based on the subjective perceptions of translation students or professionals might not adequately reflect the actual problems in the translation or interpreting process itself. Compared to more subjective perceptions, objective online measures, such as eye measures provided by eye-tracking technology, could be more accurate indicators to detect problem triggers encountered by translators and interpreters in the process. As reviewed in Sect. 2.1, eye-tracking research on sight translation has established a firm link between problem triggers and eye-movement behaviors: translation problems tend to be associated with longer fixations. The present study builds on previous work by using the eye-tracking method to document translation problems that occur in prior preparation (i.e., potential translation problems) and in the subsequent actual sight translation (i.e., actual translation problems). In particular, the eye measures of total fixation duration (TFD) and first fixation duration (FFD) were calculated for each source text word. TFD of each word was defined as “the sum of all fixation durations on a word, including the time spent rereading it” (Juhasz and Rayner 2003, p. 1313). TFD on a word in the present study was similar to the total viewing or total fixation times on a word found in existing research (Rayner et al. 2012). Longer TFD on a word indicated that the overall processing time on a word was lengthier than average and that the word was more likely a translation problem that could trigger difficulties for interpreters. FFD has been defined as “the duration of the first fixation on the word, regardless of whether the word was refixated” (Liversedge et al. 2006, p. 1727). Schaeffer et al. (2017) investigated the interaction effect of word types and translation tasks on eyemovement behaviors. Professional translators were asked to read two sets of English sentences: one set with one-to-one source text words and the other with one-to-many source text words, either for comprehension or in preparation for the subsequent actual written translation. One-to-one source text items required translations of only

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one word in German, whereas one-to-many items needed to be translated using multiple German words. They found that one-to-many items led to longer FFD than one-to-one items in the preparatory reading for the written translation. The task demand of preparatory reading for actual written translation triggered a co-activation of the source and target language, leading the researchers to believe that the translators were mentally devising possible translations in reading for translation. Moreover, the translators made greater efforts to process items requiring more than one target text word than items that required only one, and this processing occurred at the early stage. Since a one-to-many source text word lacked a shared representation in the target language, but a one-to-one source text word did not, one-to-many items were more effortful to process and therefore more problematic than one-to-one items. The results showed that more problematic words received longer FFDs than less problematic words during the preparatory reading for the actual translation task. In other words, a longer FFD on a word, at least in the early stage of the translation task such as prior preparation, is suggestive of it being a potential problem trigger for translators and interpreters. However, Neveu (2018) did not find the problem effect on FFD during sight translation from Spanish into English. Participants were asked to sight translate sentences with ambiguous words and sentences with non-ambiguous words while having their eye movements recorded to examine the effect of ambiguity on FFDs. Ambiguous words could be understood and interpreted in multiple ways and were therefore more problematic, whereas non-ambiguous words were usually interpreted in a more rigid, straightforward, or singular manner. It was expected that target text items would be co-activated early, and the selection of multiple interpretations caused by ambiguous words would lead to longer FFDs than the selection of only one interpretation caused by non-ambiguous words. However, the results revealed no significant difference between the FFD of ambiguous words and the FFD of non-ambiguous words. Taken together, the studies mentioned above provide mixed findings regarding the effect of problem triggers on FFD. Therefore, apart from TFD, FFD must also be used to detect translation problems, especially those that occur in the early stage of preparatory reading before actual sight translation. It must then be verified whether problem triggers indeed incur a greater cognitive load as measured by TFD and FFD than non-problems.

3.4.2 Problem-Solving Behaviors Problem identification and problem-solving abilities are important aspects of strategic sub-competence—strategic sub-competence being considered the most essential of all the sub-competences that constitute translation competence (PACTE 2009). Solving translation problems relies on internal or external support or the combined use of both. Internal support refers to the use of “translators’ personal worldview” (Alves and Campos 2009, p. 193), or translators’ experience and prior

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knowledge in translation (PACTE 2017), which implies the application of translators’ “internalized cognitive inputs” (Angelone 2019, p. 185). External support refers to the use of external tools and resources to help provide translation solutions. In the present study, participants are not provided with external resources throughout the entire process of sight translation. They must instead rely exclusively on their internal resources and knowledge to solve whichever translation problems arise. As discussed in Sect. 3.3.2, translation and interpreting behaviors are intercorrelated and inter-dependent, and should therefore be explored in connection with each other. Likewise, problem-solving processes are comprised of a series of interrelated behaviors that ultimately arrive at an effective solution to translation problems. PACTE (2009, 2017) investigated translators’ problem-solving behaviors via different sequences of actions used when addressing translation problems during the process. Translators’ actions were documented by the use of screen recordings and were then examined in terms of how, and to what extent, translators used their internal and/or external resources. In their definition, external support was reflected by translators’ consultations of bilingual and/or non-bilingual resources. If the translators did not consult any external resources, then they were considered to have used their internal knowledge alone. The order of these actions prior to the arrival at the solution formed sequences of translators’ actions. Four types of problem-solving behaviors could be identified based on sequences of actions: problem-solving using internal support alone, problem-solving using mainly internal support where external resources used also (but did not simply adopt the solution of bilingual resources), problem-solving using mainly external support where both bilingual and non-bilingual external resources were consulted (and solutions from bilingual resources adopted), and problemsolving using external support exclusively where translators consulted bilingual resources alone and then adopted the translation from bilingual resources as the most effective solution to a translation problem. PACTE’s model of problem-solving behaviors seems to prioritize the amount of internal and external support used over the description of how translators’ previous actions interacted with their subsequent actions before they come up with the solution to a translation problem. The degree of internal support in problem-solving behaviors in PACTE’s model is in need of further investigation. PACTE classified two types of internal support: automatized and non-automatized. The indicator of whether translators’ internal support was automatized or not was their subjective identification of translation problems in questionnaires and interviews: if a potentially difficult source text word (a rich point) was not identified as a translation problem, a translator’s use of internal support when addressing the word was considered automatized; otherwise, it was considered non-automatized due to the increased amount of inner thinking involved in this situation (PACTE 2011, 2017). As reviewed in Sect. 3.4.1, a discrepancy may well exist between subjectively perceived problems and actual problems that occur in the translation process. Therefore, the extent to which a translator uses internal cognitive resources when solving translation problems could be further examined by a more objective and online

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method, such as eye-tracking technology. Automatized internal support in problemsolving behaviors might be reflected by relatively short fixations on a potentially problematic source text word when a translator uses their internal knowledge to find its translation, while non-automatized internal support might be reflected by long fixations on a potentially difficult word. A recent study of Angelone (2018) extended PACTE’s model of problem-solving behaviors by highlighting the dynamic and interrelated nature of these behaviors found in translators themselves. In his small-scale exploratory study, Angelone (2018) examined problem awareness and problem-solving behaviors of two translation students using problem indicators documented in different stages of the translation process. These indicators included the students’ markup of anticipated translation problems in pre-translation, pauses, retrieval of external information, revision behaviors observed from screen recordings as indicators of actual translation problems in the process, and errors in the final output. The author first compared the students’ predicted problems with those of a translation trainer and found that opinions varied regarding what constituted potential problems for the subsequent actual translation task. He then compared students’ actual problems as indicated by problem indicators in on-screen activities with output errors and further examined anticipated problems, actual problems, and errors in relation to each other. One key finding was that, since most actual problems did not yield output errors, the students were able to successfully solve most of the actual problems encountered in the process of actual written translation. The author attributed the efficacy of problem-solving to the benefit of identifying potential translation problems in advance in the pre-translation task. This identification of predicted problems allowed the students to focus their attention to addressing the causes of actual translation problems themselves, as well as the resulting errors in the process of translation. The studies of PACTE (2017) and Angelone (2018) point to the importance of investigating problem-solving behaviors from interrelated perspectives. Therefore, after the identification of potential translation problems in preparatory reading, a continued examination of how these potential problems are addressed in the subsequent actual sight translation, and to what extent these potential problems could result in errors and/or disfluencies in the oral renditions, is required. Furthermore, the present study uses eye-tracking measures to examine the extent to which interpreters utilize internal support in problem-solving processes. As mentioned above, internal support in problem-solving is the application of cognitive resources to problem-solving. In the context of eye-tracking research, a higher amount of internal support, or non-automatized internal support, could be equated to the involvement of more cognitive resources in translating a source text word, compared to a lower amount of internal support, or automatized internal support. More cognitive resources could be reflected by changes in eye movements, such as longer fixations. In this sense, I would like to use cognitive resources and cognitive load, as indicated by eye-tracking measures, instead of internal support to describe how potentially problematic words identified in prior preparation are addressed in the process of actual sight translation.

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3.4.3 Problem Triggers and Coordination Behaviors After investigating problem identification and problem-solving behaviors, I shall turn to the examination of how actual problems identified in actual sight translation affect reading-speech coordination, as measured by the Max. EVS and Min. EVS. Translation problems have been found to delay coordination behaviors, as reflected by the longer ear-voice span in SI (Díaz-Galaz et al. 2015) and the longer EKS from the first fixation in written translation (Dragsted and Hansen 2008; Schaeffer and Carl 2017). More recently, Chmiel et al. (in press) conducted a study to examine the effect of visual interference in actual sight translation from English into Polish. They studied a group of interpreting trainees and compared their EVS in sight translation with their ear-voice span in SI. Since EVS was calculated from the onset of the first viewing of the source sentence, it was understood as Max. EVS. They found that the Max. EVS was significantly longer than the ear-voice span, which might indicate that the trainees started uttering the translation later in sight translation than in SI once they received the source text. The slower coordination could be explained by the higher cognitive load caused by the visual interference in sight translation. Similarly, Zheng and Zhou (2018) examined the effect of metaphorical expressions on the pace of reading ahead in the text when translation students performed sight translation from English into Chinese. They compared the EVS of metaphors and the EVS of the words which followed them. The EVS of metaphors was measured as total fixation durations on a metaphor, starting from the onset of its first fixation before its translation was uttered, and the EVS of the words which followed them was measured as total fixation durations on words after metaphors. Therefore, the EVS in their study could be understood as the Max. EVS. They found that metaphors incurred longer Max. EVS than the words that followed them. The longer EVS of metaphors showed that, compared to non-metaphorical expressions, metaphors were fixated on longer before they were interpreted due to their processing difficulty, and therefore when students read a metaphor further along the text, their speed of reading ahead was delayed. Since the behavior of reading a source text word ahead in the text before its oral rendition is conceptually similar to the coordination behavior between the first reading of a source text word and the beginning of its oral translation, Zheng and Zhou’s (2018) study provides further evidence that translation problems could delay reading-speech coordination in actual sight translation, as reflected by the longer Max. EVS of translation problems. The effect of problem triggers on Min. EVS has been underexplored in translation and interpreting studies, but oral reading research at least has been able to provide some findings on the relationship between problematic words and Min. EVS. For example, Laubrock and Kliegl (2015) found that a difficult word is a point of synchronization for the eyes and voice during oral reading of the source text: the eyes linger on the difficult word and, in so doing, wait for the voice to catch up. In other words, the eyes tend to remain on a difficult word immediately before it was pronounced.

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Another example comes from a more systematic research on word properties and EVS in oral reading. Silva et al. (2016) investigated the effect of word familiarity and word length on the offset EVS during oral reading. Offset EVS in oral reading and Min. EVS in sight translation were both calculated from the last fixation on a source text word to the onset time of its articulation in the target or source language, provided that the fixation onset was ahead of the voice onset. However, offset EVS was measured from the offset time of the last fixation, whereas Min. EVS was measured from the onset time of the last fixation. Conceptually speaking, shorter offset EVS is comparable to shorter Min. EVS as both reflect that the eyes stay closer to the word about to be articulated or interpreted in time. The offset EVS even became negative when the eyes remained fixated on a word as the voice started to pronounce it. The authors found that shorter offset EVS mostly occurred in the processing of words with lower familiarity and longer lengths, suggesting that a more difficult word was pronounced closer to its last fixation as compared to a less difficult word. The offset EVS of a difficult word was so short that the eyes still lingered on the difficult word and did not move to the following words. The findings of these two studies in oral reading seem to support the assumption that a translation of a problematic source text word tends to be verbalized soon after the eyes fixate it for the last time, and therefore problem triggers might actually lead to shorter Min. EVS than non-problems in actual sight translation. The oral rendition of a translation problem takes place so soon after its last fixation that the eyes tend not to continue moving but instead to remain on the problem word. Following the identification of potential problem triggers in advance preparation and the investigation of problem-solving behaviors in the subsequent actual sight translation, I would like to see whether actual translation problems detected in actual sight translation affect the coordination styles at a global, textual level in sight translation involving the Chinese language, as visual interference, metaphors, and unfamiliar words do, as measured by Max. and Min. EVS.

3.5 Behavioral Styles of Novice and Professional Interpreters Apart from the investigation of behavioral features common to all interpreters, this study also examines the effect of interpreting experience on behavioral styles—especially eye-movement behaviors in sight translation. This section reviews studies that investigated (a) behavioral features of novice and professional interpreters in prior preparation and in actual interpreting processes, especially at a global processing level; (b) coordination behaviors of novice and professional interpreters; and (c) problem-solving behaviors of novice and professional interpreters. Within timed readings in prior preparation before actual sight translation, behavioral differences have been observed between interpreters with varying interpreting experience. Lee (2012) studied the differences between student and professional

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interpreters in their behavioral patterns, and interpreting output and strategies when performing English to Korean sight translation. All participants were given six minutes to read a text of 600 words prior to the actual sight translation task. She found that five out of the six student interpreters failed to read the entire text within the time allocated, but all three professionals were able to do so. The findings showed that student interpreters read much more slowly than their professional counterparts in preparatory reading. Chmiel and Mazur (2013) further dug into the eye-movement patterns of firstand second-year interpreting students when performing sight translation from Polish into English. They were given ten seconds to pre-read the first page of the source text. The results of heatmaps showed that first-year students—who had received less interpreting training—scanned the text more thoroughly than second-year students. Moreover, they found that first-year students had slightly more fixations than secondyear students when pre-reading the source text, but the difference was not considered significant. The findings regarding whether more experienced interpreters sight translate faster than less experienced interpreters have been inconsistent. Most recently, Chmiel and Lijewska (2019) studied the gaze behaviors and interpreting performance of professional and trainee interpreters when sight translating subject-relative and objectrelative sentences from English into Polish, and found that professionals took significantly less time to sight translate the sentences than trainees. Lee (2012) also found that professional interpreters on average could more quickly sight translate the source text than students, but she also noticed a great variability in the actual sight translation time among professionals. Still, other studies have not found significant differences in actual sight translation times between more experienced and less experienced interpreters (Chimel and Mazur 2013; Ho 2017). Most recent studies have employed eye-tracking technology to examine the eyemovement behaviors of professional interpreters and interpreting trainees in actual interpreting processes. For example, in their eye-tracking study of SI with visual input, Korpal and Stachowiak-Szymczak (2018) investigated the eye-movement behaviors of professional and trainee interpreters when viewing PowerPoint slides with key information regarding a speech in English, which they simultaneously interpreted into Polish. The special focus of the study was related to how the interpreters processed numbers and context in the slides. One finding was that professionals produced significantly shorter mean fixation durations than trainees in processing both the numbers and context during SI, indicating that professionals invested less effort in processing visual information. Likewise, Stachowiak-Szymczak (2019) studied gaze behaviors and hand beat gestures displayed by professional and trainee interpreters during SI and CI with either pictures or a blank screen. One finding showed that professionals exhibited shorter mean fixation durations than trainees during intervals between the speaker’s articulation onset of both problematic and non-problematic items, and the end of the interpreter’s own interpretation in the mode of SI. In their follow-up study, Korpal and Stachowiak-Szymczak (2020) examined the effect of speech rate on the gaze behaviors of professional and trainee interpreters

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when processing visual information, especially with numbers in PowerPoint slides during SI. Fixation count per minute was used as the study’s eye-tracking measure to detect possible difference between the two interpreter groups when processing information throughout the slides. However, no significant between-group difference across slow and fast delivery conditions was observed. In his eye-tracking study of English–Chinese sight translation, Ho (2017) examined the effect of both interpreting experience and task types on interpreters’ gaze behaviors and interpreting performance. During the sight translation task, the participants were allowed to pre-read the translations of difficult terms in the source text that was to be sight translated. Fixation count was used to examine global processing patterns between the different interpreter groups, but the author did not find a noticeable difference in the number of fixations on the source text between experienced and student interpreters—a finding similar to that of the aforementioned study by Korpal and Stachowiak-Szymczak (2020). Taken together, previous studies have focused their research on the examination of behavioral differences between interpreters with varying experience in preparatory reading and adopted limited eye measures to examine global processing behaviors. It remains unclear how professionals and novices allocate their time in preparatory reading and the subsequent actual sight translation in rehearsed sight translation, and as such, there is a need to further study how the two interpreter groups vary in their gaze behaviors in preparatory reading and actual sight translation with the use of more eye-tracking measures. Aside from global reading patterns, the present study also examines patterns of reading-speech coordination and identifies possible behavioral differences between professional and novice interpreters in relation to this aspect. Evidence for how interpreting experience affects coordination between comprehension and production remains mixed. Díaz-Galaz et al. (2015) did not observe significant differences in ear-voice span between experienced and student interpreters in either SI with prior preparation or SI without prior preparation. However, translation experience was found to affect reading-typing coordination in written translation. Dragsted (2010) examined how professional and student translators coordinated reading and typing using EKS from first fixation and EKS from last fixation. She found that students had a longer EKS from first fixation than professionals. During students’ longer EKS from first fixation on a source text word, several pauses, along with a number of refixations on the word itself and those close to it, were observed before its translation was typed. She found fewer pauses and refixations on a source text word during professionals’ much shorter EKS from first fixation. The findings showed that translation experience did affect the speed of input–output coordination: more experienced translators had a faster transformation than less experienced translators between the first reading of the source text word and the first typing of its translation. Schaeffer and Carl (2017) replicated Dragsted’s (2010) study with a larger dataset and found similar results: students had a significantly longer EKS from first fixation than professionals. The longer EKS from first fixation of translation students in these studies has been interpreted as a less efficient, and more hesitant,

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transformation from the first contact of the source text to the typing of its translation due to a lack of practice and experience. Translation experience could also influence the extent of context planning as the translation is delivered. In their eye-tracking and key logging study of written translation, Dragsted and Carl (2013) examined the translation styles of student and professional translators in different stages of written translation. Coordination styles were primarily examined via qualitative analyses of the translation progression graphs obtained. The graphs highlighted that some translators’ fixations were relatively further ahead of the word being translated, meaning that they tended to read a large context ahead before, or during, the typing of the translation, and were thus categorized as broad-context planners. Conversely, some translators’ fixations were much closer to the word being typed, and their fixations frequently overlapped with typing activities, showing that they preferred to read a smaller context ahead as they typed the translation, leading these translators to be classified as narrow-context planners. When translation experience was considered, the authors found that approximately half of the students exhibited the style of broad-context planners, while slightly more than a half of the professionals demonstrated the style of narrow-context planners, although this trend was not found to be very strong. Dragsted et al. (2009) examined the translation behaviors of three professional translators with varying years of experience when performing different translationrelated tasks, including sight translation. The percentage of on-sync fixations (i.e., fixations on the word being translated) and off-sync fixations (i.e., fixations before or after the word being translated) were used as indicators of planning activities as translators uttered the translation in actual sight translation. They found that the professional translator with most translation experience had a higher percentage of off-sync fixations while the other two professionals with the least translation experience had a higher percentage of on-sync fixations. The most experienced translator could be said to have engaged himself in a broader context as the translation was delivered, whereas the less experienced translators preferred not to allow their eyes to stray too far from the word being orally translated. However, the authors also noticed that the narrower context planning activities of less experienced translators were accompanied by more pre-planning activities before producing the translation of each sentence. The findings of previous studies have been inconsistent in explaining how translation and interpreting experience influence coordination behaviors in terms of coordination speed and the extent of planning behaviors during input–output coordination. Furthermore, indicators such as on-sync and off-sync fixations might be insufficient in describing the planning activities when no oral rendition is produced, and therefore the present study sees fit to adopt the eye-voice latency—especially the latency from the onset of the first fixation on a source text word—so as to better examine the possible differences in planning behaviors during coordination. Since interpreters are able to read a source text word multiple times before having to utter its translation, it was also worth examining reading-speech coordination behaviors from the last fixation on a source text word to the delivery of its translation. As reviewed above, Dragsted (2010) also studied EKS from last fixation and found

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that students had a longer EKS from last fixation than professionals. Jakobsen (2017) interpreted professionals’ shorter EKS from last fixation as a preference for updating working memory immediately prior to the delivery of the translation. The present study investigates coordination behaviors from when a source text word was last read to the onset of its oral rendition in a different translation mode, namely sight translation. After examining the experience effect on global translation behaviors at the textual level, the present study also seeks to investigate the effect of interpreting experience on local translation behaviors at specific problem triggers. Olalla-Soler (2019) drew on PACTE’s (2017) model of problem-solving behaviors to investigate how student and professional translators differed in solving cultural translation problems from German into Spanish. As mentioned in Sect. 3.4.2, PACTE’s model categorized four types of problem-solving behaviors based on the observation of translators’ use of internal and/or external support from screen recordings. Professionals used internal support alone most frequently, while students predominantly opted for external support and external support alone to address cultural problems. Professionals’ dominant use of internal support alone led to the highest levels of translation acceptability. Conversely, the students’ dominant use of external support and external support alone led to the worst levels of acceptability, but their less frequent use of internal support led to better translation outputs. The results demonstrated professionals’ efficient use of internal support to address cultural problem triggers in written translation. As mentioned above, Korpal and Stachowiak-Szymczak (2018) found that professional interpreters exhibited significantly shorter average fixation durations than novices when simultaneously interpreting numbers—the problem triggers that appeared in the PowerPoint slides during SI with text. Professionals were also found to be able to interpret numbers more accurately than novices. The results showed professional interpreters as displaying more effective and efficient problem-solving behaviors. The present study attempts to provide further evidence on the effect of interpreting experience on problem-solving behaviors in sight translation—particularly when interpreters rely exclusively on their own internal support to solve potential translation problems from Chinese into English, using objective, online eye-tracking measures. Moreover, considering the importance of investigating the interrelated nature of interpreting behaviors, I also explore how novice and professional interpreters address potential problems identified in preparatory reading in the subsequent stage of actual sight translation.

3.6 Summary To sum up, translation style has been more deeply studied in the context of written translation. Little attempt has been made to examine the issue in other modes of translation (e.g., sight translation). Furthermore, existing studies have approached

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the issue by analyzing translations between European languages, which in general are linguistically close to one another. Little effort has been made to investigate translation styles between vastly linguistically different languages, namely Chinese and English. Therefore, the present study focuses on translation styles in sight translation between Chinese and English by using eye-tracking technology in order to fill this knowledge gap.

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Holmqvist, K., Nyström, M., Andersson, R., Dewhurst, R., Jarodzka, H., & Van de Weijer, J. (2011). Eye tracking: A comprehensive guide to methods and measures. Oxford: Oxford University Press. Huang, J. (2018). Working styles of student translators in self-revision, other-revision and postediting. In C. Walker, & M. Federico Federici (Eds.), Eye tracking and multidisciplinary studies on translation (pp. 145–184). Amsterdam/Philadelphia: John Benjamins Publishing Company. Hvelplund, K. T. (2017). Four fundamental types of reading during translation. In A. L. Jakobsen, & B. Mesa-Lao (Eds.), Translation in Transition: Between cognition, computing and technology (pp. 55–77). Amsterdam/Philadelphia: John Benjamins Publishing Company. Inhoff, A. W., Solomon, M., Radach, R., & Seymour, B. A. (2011). Temporal dynamics of the eye–voice span and eye movement control during oral reading. Journal of Cognitive Psychology, 23(5), 543–558. https://doi.org/10.1080/20445911.2011.546782. Jakobsen, A. L. (2002). Translation drafting by professional translators and by translation students. In G. Hansen (Ed.), Empirical translation studies: Process and product (pp. 191–204). Frederiksberg: Samfundslitteratur. Jakobsen, A. L. (2003). Effects of think aloud on translation speed, revision and segmentation. In F. Alves (Ed.), Triangulating translation: Perspectives in process oriented research (pp. 69–95). Amsterdam/Philadelphia: John Benjamins Publishing Company. Jakobsen, A. L. (2017). Translation process research. In J. W. Schwieter, & A. Ferreira (Eds.), The handbook of translation and cognition (pp. 21–49). West Sussex: Wiley-Blackwell. Juhasz, B. J., & Rayner, K. (2003). Investigating the effects of a set of intercorrelated variables on eye fixation durations in reading. Journal of Experimental Psychology. Learning, Memory, and Cognition, 29(6), 1312–1318. https://doi.org/10.1037/0278-7393.29.6.1312. Kader, S., & Seubert, S. (2015). Anticipation, segmentation…stalling? How to teach interpreting strategies. In D. Andres, & M. Behr (Eds.), To know how to suggest… Approaches to teaching conference interpreting (pp. 125–144). Berlin: Frank and Timme. Kajzer-Wietrzny, M. (2013). Idiosyncratic features of interpreting style. New Voices in Translation Studies, 9(1), 38–52. Kalina, S. (2015). Preparation. In F. Pöchhacker (Ed.), Routledge encyclopaedia of interpreting studies (pp. 318–320). London and New York: Routledge. Korpal, P., & Stachowiak-Szymczak, K. (2018). The whole picture: Processing of numbers and their context in simultaneous interpreting. Poznan Studies in Contemporary Linguistics, 54(3), 335–354. https://doi.org/10.1515/psicl-2018-0013. Korpal, P., & Stachowiak-Szymczak, K. (2020). Combined problem triggers in simultaneous interpreting: Exploring the effect of delivery rate on processing and rendering numbers. Perspectives, 28(1), 126–143. Krings, H. P. (1986). Translation problems and translation strategies of advanced German learners of French (L2). In J. House & S. Blum-Kulka (Eds.), Interlingual and intercultural communication: Discourse and cognition in translation and second language acquisition studies (pp. 263–276). Tübingen: Gunter Narr Verlag. Künzli, A. (2009). Think-aloud protocols–A useful tool for investigating the linguistic aspect of translation. Meta, 54(2), 326–341. https://doi.org/10.7202/037684ar. Lambert, S. (2004). Shared attention during sight translation, sight interpretation and simultaneous interpretation. Meta, 49(2), 294–306. https://doi.org/10.7202/009352ar. Laubrock, J., & Kliegl, R. (2015). The eye-voice span during reading aloud. Frontiers in psychology, 6, 1432. https://doi.org/10.3389/fpsyg.2015.01432. Lee, J. (2012). What skills do student interpreters need to learn in sight translation training? Meta, 57(3), 694–714. https://doi.org/10.7202/1017087ar. Lee, T.-H. (2002). Ear voice span in English into Korean simultaneous interpretation. Meta, 47(4), 596–606. https://doi.org/10.7202/008039ar. Li, D. (2017). Translator style: A corpus-assited approach. In M. Ji, M. Oakes, D. Li, & L. Hareide (Eds.), Corpus methodologies explained: An empirical approach to translation studies (pp. 103– 136). London: Routledge.

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Chapter 4

Eye-Tracking Method

Abstract The previous chapters have outlined the research background and reviewed relevant literature on translation styles. This chapter aims to present details of the research design in order to explore possible behavioral patterns in sight translation. Eye-tracking method will be the research tool in this project. In this chapter, I will first describe the indicators for each research question in Sect. 4.1. Following that, the process of data collection, including the recruitment of research participants, the application of the eye tracker, the selection of experimental stimuli, and the procedure of the sight translation task will be discussed in Sect. 4.2. Finally, the process of how the data collected in the present experiment will be analyzed will be discussed in Sect. 4.3. Keywords Eye-tracking method · LMER · Indicators of research questions · Experimental stimuli · Experimental procedure

4.1 Eye-Tracking Indicators Previous sections of this book have reviewed the existing literature on behavioral styles in different modes of translation. The investigation of different behavioral styles and features is indeed the major theme within the behavioral approach to CITS. However, behavioral characteristics, especially patterns of gaze behaviors in sight translation, have yet to be fully examined. The study therefore attempted to investigate eye-movement behaviors in the mode of prepared sight translation and to summarize gaze patterns common to all interpreters while also doing so for those patterns specific to novice or professional interpreters. For that purpose, a list of eye-movement indicators, together with the indicators of interpreting outputs, was presented for each of the six research questions in Table 4.1, with an overall aim to identify behavioral styles in sight translation.

© The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2020 W. Su, Eye-Tracking Processes and Styles in Sight Translation, New Frontiers in Translation Studies, https://doi.org/10.1007/978-981-15-5675-3_4

49

50

4 Eye-Tracking Method

Table 4.1 Research questions and their indicators Research questions

Indicators

(1) How are eye-movement behaviors affected by the two different stages of sight translation? Do novice and professional interpreters exhibit different gaze behaviors in each of the two stages?

TT of the text FC of the text SA of the text FD on the text PD on the text

(2) How do the gaze behaviors displayed in advance preparation correlate with the gaze behaviors exhibited in the subsequent actual sight translation? Does the correlation vary between novice and professional interpreters?

TT of prep and TT of actual FC in prep and FC in actual SA in pre and SA in actual FD in prep and FD in actual PD in prep and PD in actual

(3) How do novice and professional interpreters coordinate reading and speaking in actual sight translation, as measured by the eye-voice span at the textual level?

Max. EVS of the text Min. EVS of the text

(4) What common potential problems in advance preparation can be identified for novice and professional interpreters?

FFD on each source text word in prep TFD on each source text word in prep

(5) What happens to the potential problem TFD on each source text word in actual triggers in actual sight translation? Do Production errors, disfluencies, and omissions novice and professional interpreters display of each source text word different behaviors when solving the potential problems in actual sight translation? (6) How do translation problems affect the coordination styles?

Max. EVS of each problem trigger and non-trigger Min. EVS of each problem trigger and non-trigger

prep = prior preparation stage; actual = actual sight translation

4.2 Data Collection Eye-tracking experiments were conducted with two groups of interpreters (one novice, one professional) on sight translation from Chinese into English. The experiments were conducted at a Macau tertiary institution from July to December 2018. The following gives details about the research participants, the apparatus used to gather the eye data and oral translations, the materials as stimuli, the procedures of the experiments, and the follow-up interview.

4.2 Data Collection

51

4.2.1 Participants Thirteen novice interpreters (N01–N13, mean age = 26, SD = 4.4) and nine professional interpreters (P01–P09, mean age = 33.44, SD = 7.58) participated in the study (Tables 4.2 and 4.3). As reviewed above, the similarities between sight translation and SI are due to the fact that interpretations are expected to be produced simultaneously with comprehension. Therefore, great efforts were made to invite professional interpreters to participate in the experiment. Nine professional interpreters were recruited, all of whom had a minimum of four years of interpreting experience. Besides, thirteen novice interpreters were also recruited. These novices were second year and third year MA translation and interpreting students at a Macau tertiary institution at the time of the experiment, or former students from the university (and other universities) now working as freelance translators and interpreters. At the time of the experiment, they all had no more than one year of interpreting experience. The participants’ language proficiency and translation competence were assessed based on self-ratings of their Chinese proficiency, English proficiency, and translation competence (see García et al. 2014) on a scale of 0–10 (0 = none, 10 = optimal). To ensure within-group similarity, outliers of language proficiency (the average value of Chinese and English proficiency) and translation competence within each group were detected using the 1.5 interquartile range rule. As a result, both participant groups had a similar within-group language proficiency and translation competence. Table 4.4 summarizes their average Chinese proficiency, English proficiency, and translation competence. The t-test showed a significant difference between novice Table 4.2 Profile of the Novice Interpreters Participant

Sex

Education

Interpreting experience

N01

F

MA in Translation Studies, second year

≤1 year

N02

M

MA in Translation Studies, third year

≤1 year

N03

F

MA in English Literature

≤1 year

N04

F

MA in Translation Studies

≤1 year

N05

F

MA in Translation Studies, third year

≤1 year

N06

F

MA in Translation Studies, second year

≤1 year

N07

F

MA in Translation Studies, second year

≤1 year

N08

F

MA in Translation Studies

≤1 year

N09

F

MA in Translation Studies, second year

≤1 year

N10

M

MA in Translation Studies, third year

≤1 year

N11

F

MA in Translation Studies, second year

≤1 year

N12

M

MA in Translation Studies, second year

≤1 year

N13

F

MA in Translation Studies, second year

≤1 year

52

4 Eye-Tracking Method

Table 4.3 Profile of the professional interpreters Participant

Sex

Education

Interpreting experience

P01

F

MA in Interpreting and Translation

≥4 years

P02

M

Ph.D. in Translation Studies

≥4 years

P03

F

MA in Translation and Interpreting Studies

≥4 years

P04

M

Master of Translation and Interpreting (MTI)

≥4 years

P05

M

BA in English Literature

≥4 years

P06

F

Master of Translation and Interpreting (MTI)

≥4 years

P07

M

MA in Translation and Interpreting Studies

≥4 years

P08

F

MA in Translation and Interpreting

≥4 years

P09

M

Master of Translation and Interpreting (MTI)

≥4 years

Table 4.4 Language proficiency and translation competence of participants

Group

Chinese proficiency

English proficiency

Translation competence

Novice

8.31 (SD = 0.85)

7.38 (SD = 0.65)

6.46 (SD = 0.52)

Professional

8.67 (SD = 0.71)

8 (SD = 0.71) 7.67 (SD = 0.5)

and professional interpreters in self-rated English proficiency (p < 0.05) and translation competence (p < 0.001). There was no significant difference found between the two groups in Chinese proficiency.

4.2.2 Materials Four Chinese source texts (Appendix) were selected from the book Xi Jinping: the Governance of China II (习近平谈治国理政[第二卷]) (Xi 2017), a collection of President Xi Jinping’s speeches on different topics. For the purpose of the present research, the source texts were shortened and adapted according to the following three criteria. First, each text had to be deemed natural and semantically coherent. Second, each text had to contain a number of translation problems that could trigger higher cognitive load and output errors, or disfluencies for the participant. Third, the four texts needed to be comparable in terms of word count, number of sentences, lexical variability, and the number of lines (Table 4.5). Lexical variability was calculated as the percentage of the unique words in the running words. In addition, expert opinion

4.2 Data Collection

53

Table 4.5 Text profiling Parameters/text

Text 1

Text 2

Text 3

Text 4

Topic

Community of shared future

Belt and Road Initiative

Chinese socialism

Economic globalization

Words (characters)

113 (209)

111 (197)

111 (203)

114 (205)

Sentences

6

6

6

6

Lexical variability

0.72

0.7

0.73

0.73

Lines

11

11

10

10

was also sought regarding the difficulty of the texts. A professor of Chinese language and a professor of translation studies were invited to read the four texts and judge the difficulty of the texts. They both considered the texts to be comparable in terms of difficulty.

4.2.3 Apparatus and Presentation of Stimuli The stimuli were presented on a 23 LCD screen with a 1920 × 1080 pixel resolution, at a viewing distance of approximately 65 cm. Eye movements were recorded with a Tobii TX300 Eye Tracker (sampling rate = 300 Hz, spatial accuracy = 0.4°–0.9°). Tobii StudioTM version 3.4.8 software was used to present the stimuli and export the gaze data and recordings of the sight translations for analysis. The Chinese stimuli were displayed in Microsoft YaHei font size 19 with double line spacing. Double line spacing was considered sufficient to assign the fixations to the proper text lines. The texts were all single paged. A Latin square design was used to counterbalance the presentations of the four source texts.

4.2.4 Procedure Participants were tested individually in a quiet laboratory. They first signed an informed consent form and asked to rate their Chinese proficiency, English proficiency, and translation competence on a 0–10 scale (0 being the lowest and 10 the highest). They were then told to sight translate four Chinese texts from President Xi Jinping’s speeches into English. The whole experiment was labeled “Project” and comprised of four trials, each with four PDF documents labeled “Intro 1”, “Preparation”, “Intro 2”, and “Actual” (Fig. 4.1). The PDF document named “Preparation” presented one Chinese source text, and the PDF document named “Actual” presented the same source text in the same trial. They were told that, once the experiment started, they would see an instruction page with the words, “You are going to see an extract from President Xi Jinping’s

54

4 Eye-Tracking Method

Fig. 4.1 Project structures in Tobii Studio

speech. Please read the text in preparation for the subsequent sight translation. When you finish reading and feel you are ready to sight translate the text, say ‘Okay’”. Participants had no more than 15 min to pre-read each source text before the commencement of the actual sight translation. I then pressed the key and the source text appeared on the screen. On hearing the “Okay” from the participants, I pressed another button and a new introduction page appeared, saying “Please sight translate the text.” The participants then sight translated the text presented on the screen. They were instructed to produce the translations as completely as possible. The participants were each asked to sit comfortably in front of the eye tracker and to wear an earphone with a mouthpiece so that their oral translations could be recorded. Each participant went through a calibration procedure, and the recording would not begin until the calibration result was deemed satisfactory. The same calibration procedure was repeated before each test. There was a short break of approximately 2 min between each trial. After sight translating the four texts, the participants were asked to review the recordings of their sight translations with the gaze data of each text, together with the researcher. The purpose of the follow-up interview was to verify with the participants any ambiguities or inaudible words and expressions in the recordings and to ask them any questions I might have had with regard to the experiment. They were free to make any comments while viewing the replay. The interviews were audio recorded with an external recorder.

4.3 Data Analysis

55

4.3 Data Analysis This section reports how the eye-movement data and the sight translation output will be analyzed. First presented are the procedures implemented so as to guarantee eye data quality and a summary of the guidelines of conducting LMER analysis, followed by detailed descriptions of how the data will be analyzed for each research question.

4.3.1 Eye Data Quality When obtaining eye measurements, fixation duration was calculated via Tobii I-VT Fixations Filter, meaning that fixations shorter than 60 ms were discarded. Prior to the analysis, the eye data quality was also assessed in regard to its accuracy and robustness (Holmqvist et al. 2011). Accuracy was checked with the gaze plot function in Tobii Studio. Robustness, which refers to the proportion of data loss (Holmqvist et al. 2011), was assessed by the percentage of valid gaze samples calculated by Tobii Studio (Tobii Pro 2017). A higher percentage of valid gaze samples translated to a larger number of eye-tracking samples having been correctly identified on the screen. The percentage of valid gaze samples was similar to the percentage of gaze time on screen proposed by Hvelplund (2014). Recordings with at least 80% of valid gaze samples were selected for further analysis. The 80% threshold was chosen so as to select recordings with eye data of relatively high quality. The percentage of valid gaze samples of each participant is presented in Table 4.6.

4.3.2 General Guidelines for Conducting LMER Analysis An LMER was conducted for the analysis of translation styles and cognitive effort in sight translation using the lme4 package (Bates et al. 2015) in the statistical software R 3.5.2 (R Core Team 2018). I took a six-step process to conduct the LMER analysis. The procedures of construction and simplification of random effect structures in Step 4 mostly adhered to the study of Bates et al. (2018). First, I identified the dependent variables, independent variables, and random factors for the LMER analysis. In the present study, the random factors always constituted participants and items. Items refer to either texts or words based on the research questions. Special attention was paid to the variables that needed to be statistically controlled. Second, distributions of the dependent variables were checked based on visual inspection, and dependent variables that had skewed distributions were logarithmically transformed to achieve normal distribution. The quantile-quantile plots of each participant were checked so as to detect possible outliers before building the model

56

4 Eye-Tracking Method

Table 4.6 Percentage of valid gaze samples Participant/Text

Gaze samples Text 1 (%)

Text 2 (%)

Text 3 (%)

Text 4 (%)

N01

90

85

84

83

N02

92

91

88

86

N03

83

88

90

88

N04

93

92

94

95

N05

93

96

94

94

N06

93

97

96

93

N07

97

98

97

97

N08

87

88

89

91

N09

89

88

88

89

N10

93

93

92

93

N11

87

87

88

87

N12

93

91

93

96

N13

93

94

92

93

P01

89

90

87

87

P02

97

97

98

97

P03

93

96

90

96

P04

99

99

98

99

P05

99

97

99

99

P06

96

95

97

96

P07

99

94

94

90

P08

96

96

96

96

P09

99

99

99

99

(Baayen 2008). Mild initial data trimming was applied if obvious outliers were found (Baayen and Milin 2010). Third, I specified the fixed and random effects of each LMER model for each dependent variable based on the research design and research questions and built the model with a maximal random effects structure. For the fixed effects structure, deviation coding was used to obtain the main effects when there was more than one categorical predictor (e.g., group and stage) contained in the LMER model. When specifying the random effects structure, random slopes that made sense for the experimental design were fully considered. Although most prior studies researching translation processes seem to include only random intercepts in the random effects structure, models including random slopes justified by the research design are highly important and may better serve to avoid anti-conservative results than random intercepts models (Barr et al. 2013). Fourth, I inspected the full random effects structure by performing a principal components analysis of the random effects and removed the components that

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57

explained less than 1% of variance (Bates et al. 2018). If the resulting model still did not converge, it indicated that the current dataset was not sufficiently large to support the inclusion of certain random slopes. As Bates et al. (2018) explained when building models with maximal random structures, “failure to converge is not due to defects of the estimation algorithm, but is a straightforward consequence of attempting to fit a model that is too complex to be properly supported by the data” (p. 19). As such, I continued to simplify the random structure by dropping the component that explained the smallest variance until the model converged. Fifth, collinearity between the predictors of the resulting model was detected by the variance inflation factor (VIF), and the assumptions of each model were checked by a visual inspection of the model criticism plots using the mcp.fnc function from the LMERConvenienceFunctions package (Tremblay and Ransijn 2015). Data points with large absolute standardized residuals were removed to improve model prediction wherever necessary (Balling et al. 2014). Sixth, the results of the LMER analysis were obtained using the lmerTest package (Kuznetsova et al. 2019). P values in the LMER output were calculated using the Satterthwaite approximation. Pairwise comparisons of the interaction term in each model were obtained using the difflsmeans function in the lmerTest package (Kuznetsova et al. 2019). Pairwise comparisons of interaction in Poisson regression were estimated using the emmeans package (Lenth et al. 2019).

4.3.3 Data Analysis for Global Style 1 A series of LMER analyses were performed to investigate the first aspect of global translation styles, i.e., how stages of sight translation influence the gaze behaviors of interpreters and whether interpreting experience affects the gaze patterns observed in each stage. The whole text was used as the unit of analysis, and five global measures were computed: TT, FC, SA, FD, and PD. These five global measures were dependent variables. The first factor (or independent variable) was group, namely the groups of participants. These were either novice interpreters (Nov) or professional interpreters (Pro). The second factor was stage, which consisted of preparation (Stage 1) and actual sight translation (Stage 2). The main effects of group, stage, and their interaction were entered into each LMER model. Poisson regression was used for the FC model as it was a count variable. Scanpaths in preparation and actual sight translation were visualized using Excel to identify different reading styles.

4.3.4 Data Analysis for Global Style 2 Other LMER analyses were conducted to explore the second aspect of global translation styles, i.e., how the gaze behaviors in advance preparation affect the gaze

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behaviors in actual sight translation, and whether the influence varies between the two groups. The dependent variables were identified as five global measures observed in Stage 2 of the actual sight translation, namely TT2, FC2, SA2, FD2, and PD2. The independent variables were the corresponding five global measures observed in Stage 1 of preparation, namely TT1, FC1, SA1, FD1, and PD1. Originally, group (Nov. vs. Pro) and the interaction between group and each of the five measures observed in preparation were included as predictors in each LMER model to examine whether the influence of the gaze behaviors in preparation on the gaze behaviors in actual sight translation differed between the two groups. However, the VIF of group and the interaction term in the SA, FD, and PD models were significantly high (16 and 16.65; 15.51 and 16.75; 89.98 and 86.42, respectively). Since high VIF is indicative of collinearity between predictors and could therefore make the results unreliable, the five global measures observed in preparation were kept as predictors solely in the final LMER models. LMER analysis was conducted for novices and professionals separately.

4.3.5 Data Analysis for Global Style 3 LMER analyses were conducted to examine the third aspect of global translation styles, i.e., how novices and professionals coordinated reading and speaking in actual sight translation, as measured by the EVS at the textual level. The dependent variables at this level were Max. EVS and Min. EVS. The test predictor was group with two levels (novices vs. professionals), and the task time that the participants spent in preparation was included as the control predictor. Since the Max. and Min. EVS of each text was the average value of the Max. and Min. EVS of each source text word in each text, I first calculated the EVS of each word. A three-step process was required to accomplish this. First, each fixation of each participant when sight translating each text was mapped onto the corresponding source text word. The gaze data exported by Tobii Studio contained information on each fixation, such as its fixation duration and its onset timestamp, but unlike Translog—which automatically identifies words on which each fixation is registered with the gaze-to-word mapping tool (Carl 2008)—the gaze data obtained from Tobii Studio did not explicitly identify which word the participant was fixating at a particular moment in time. As a result, it was necessary to develop a method to combat this limitation and map each fixation on the corresponding source text word. One solution was to watch the gaze plot of each participant throughout their sight translation of each text and record the position by hand, i.e., the source text word on which each fixation was located. This method was considered to be both laborious and time consuming, and the mapping may have been lacking in accuracy since each fixation point of each fixation was too small to observe its location simply by visual inspection. Another solution was to map each fixation on each word by matching their spatial locations as measured by the XY coordinates. This solution proved to be much more efficient, and the mapping was considered more reliable as each fixation could

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be objectively mapped into the coordinate system provided by Tobii Studio. The results of this mapping were further verified with the gaze plot of each participant. After the first step, the eye data with information on the onset timestamp and duration of each fixation, fixation sequence, and the corresponding source text word on which the fixation was registered was prepared for further analysis. Second, oral renditions of each source text word were transcribed and coded. The eye data obtained from the afore-mentioned first step had provided information on the beginning of the first fixation on each source text word. It was then necessary to know the onset time of the oral rendition of each source text word so as to calculate the EVS. The oral renditions were transcribed by the automatic sound recognition (ASR) server of IMB Watson, and the resulting transcriptions contained information on the onset and offset timestamp of each target text word. Since the transcriptions produced by ASR were typically not entirely accurate, it was considered necessary to check them against the audio recordings to ensure that the transcriptions were both accurate and complete. Following on from this, each target text word was coded into the corresponding source text word. The second step completed, and the voice data with information on the onset and offset timestamp of each target text word and their corresponding source text word was prepared for analysis. Third, the voice data was joined with the eye data to calculate the EVS of each source text word by running a series of commands in R. Since the present study only considered instances where the reading of a word preceded its oral rendition, the observations where the onset timestamps of the fixations appeared later than the onset timestamps of the voice were not included in the calculations of the EVS. The final output contained information on the Max. and Min. EVS of each source text word of each participant when sight translating each text. To recap, the Max. and Min. EVS of each text was the mean value of the Max. and Min. EVS of each word in each text. To visualize the distance between the eyes and the voice over time during the sight translations of the whole text, bubble graphs in Excel were created to illustrate the data of Max. and Min. EVS at the textual level. To further examine the eyemovement behaviors during the oral renditions of the text, scanpaths and translation outputs were synchronized using ELAN.

4.3.6 Data Analysis for Local Style 1 For local translation styles, I divided the data into the preparation and actual sight translation stages and compared the local translation styles of novices and professionals within and between each stage. To examine the first aspect of local translation styles, i.e., to identify what source text words could potentially cause translation problems for the participants, the gaze data within advance preparation was analyzed. Specifically, I drew up each word as an area of interest (AOI), used them as the unit of analysis, and calculated two local measures: first fixation duration (FFD) and total fixation duration (TFD) of each word. I then selected those words with the 5 longest

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FFDs or the 15 longest TFDs by each participant. These FFD and TFD values served as thresholds intended to identify words that caused relatively high cognitive effort as measured by FFD or TFD for each participant and therefore became identified as anticipated translation problems. On top of the “5 longest FFD” and “15 longest TFD” thresholds, a further rule was applied: common potential problems should include the words on which at least four out of the thirteen novice interpreters or those on which at least three out of the nine professional interpreters registered the 5 longest FFDs or the 15 longest TFDs. I then compared the common potential problem triggers between novices and professionals. Translation problems could be classified into different groups based on linguistic levels (Lörscher 1991; Shreve et al. 2011) or processing features (Ivanova 2000; Angelone 2018). Since one of the research purposes is to examine how interpreters processed a discourse with Chinese characteristics, the potential problems that were identified in preparation were categorized according to whether they were words with Chinese features. As a result, the potential problems included words and expressions with Chinese features, as well as ordinary words. Words and expressions with Chinese features were further classified into political and traditional words. As with any effort of categorization, overlapping occurred in the process of concretely establishing words and expressions with Chinese characteristics. Therefore, I relied on the official Web site Corpus of Standardized Translations of Important Political Expressions with Chinese Characteristics (中国重要政治词 汇对外翻译标准化专题库 [http://210.72.20.108/special/class3/search.jsp]) as the ultimate reference. That is, all political words with Chinese features had to have been in the abovementioned database. As a result, 301 words with Chinese characteristics, including 295 political words and six traditional words, were identified in the four source texts (Appendix). In order to investigate whether each group indeed spent extra time fixating the common potential problems in advance preparation, an LMER analysis was conducted to compare the FFD and TFD on common potential problems and nonproblems in each group. The dependent variables were FFD and TFD on word level, and the test predictor was AOI with two levels (common potential problems [CPPs] versus common potential non-problems [CPNPs]). Such results would be able to indicate to the author whether the participants had already started mentally translating the potential problems in the preparation stage. Following the identification of the potential problems in each group, I further selected those CPPs that were encountered by both novices and professionals and used another LMER analysis to investigate whether their effects as perceived by both groups on FFD and TFD varied between novices and professionals. Thus, group, AOI (common potential problems for both groups [CPPFBGs] vs. common potential nonproblems for both groups [CPNPFBGs]), and their interaction were entered as the predictors in this LMER model.

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4.3.7 Data Analysis for Local Style 2 To examine the second aspect of local translation styles, i.e., how the two groups addressed the potential translation problems identified in the advance preparation, I further analyzed the gaze data and the oral productions in the subsequent stage of actual sight translation. Specifically, the TFD and oral outputs by each participant of the potential problems identified in each text during the preparation stage were examined. FFD was not examined for the processing patterns in the stage of actual sight translation due to the participants having read the text for a second time in this stage, so strictly speaking, FFD was not the duration when the participants fixated the word for the first time. I classified the potential problems into different groups according to their TFD values in actual sight translation. A potential problem was labeled as high TFD if found in the list of the 15 longest TFD words by each participant when sight translating each text in actual sight translation; otherwise, it was labeled as low TFD. An examination of the oral output of the potential problems followed. The participants may have interpreted them correctly, incorrectly, and/or disfluently. They may also have produced no interpretation. Therefore, each potential problem that was identified in advance preparation may have resulted in high TFD with disfluent and/or incorrect output, high TFD with no output, high TFD with correct output or low TFD with disfluent and/or incorrect output, low TFD with no output, and low TFD with correct output in the subsequent actual sight translation (Table 4.7). In fact, anticipated problems of high TFD with correct production and those of low TFD with incorrect production were similar to what Krings called “problems without errors” and “errors without problems” (1986, p. 267). He found that translation students occasionally verbalized some words as problems but would go on to translate them correctly, yet at other times would make mistakes in translating some words which had not been explicitly verbalized as problems. Likewise, in the present study, some potential problems that were identified in prior preparation were found to be remained fixated for a relatively long period of time in actual sight translation but were translated correctly. Conversely, some potential problems were not fixated for a long period of time in actual sight translation but still resulted in errors. Krings (1986) stated that such features of translation problems might not be easily found by product analysis alone but could be identified when the problem indicators from the translation processes were also taken into consideration. The oral output of sight translation was assessed in terms of disfluencies, errors, and omissions. Disfluencies included pauses and repairs (Shreve et al. 2011). Given that participants naturally had different production speeds and thus different pause patterns (see Dragsted 2005), flexible pause thresholds could serve as better alternatives to the fixed pause threshold. Therefore, three pause thresholds—three seconds, two seconds, and one second—were established based on participants’ rendition speed of each text within each group. If a source text word or segment caused a pause that exceeded the threshold, it was considered to cause a major pause and thus a disfluency in the oral output.

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Table 4.7 Classification of what potential problems in stage 1 would be like in stage 2 Potential problems in stage 2

Oral output

Possible explanation

Relatively high TFD

Incorrect and/or disfluent

Suggesting that the potential problem remained problematic, and the interpreter struggled with it but was not able to eventually solve it, resulting in incorrect translations, and/or they were not able to solve it smoothly, resulting in disfluent production

No production

Suggesting that the potential problem remained problematic, and the interpreter struggled with it but gave up on it possibly due to time pressure

Correct

Suggesting that the potential problem remained problematic, and the interpreter made efforts to solve it and succeeded

Incorrect and/or disfluent

Suggesting that the interpreter might have felt they solved the problem in preparation, but actually, it was still a problem for them, resulting in disfluent and/or incorrect translations

No production

Suggesting that the interpreter struggled with it in preparation and finally decided to omit it from the subsequent actual sight translation, resulting in no production

Correct

Suggesting that the potential problem was no longer problematic in the subsequent actual sight translation, and the interpreter solved the problem successfully, resulting in correct production

Relatively low TFD

A problematic pause could be a pause before a segment or a pause before a word or phrase. A pause before a segment is demonstrative of processing difficulties of the segment, while a pause before a word or phrase suggests processing difficulties relating to said word or phrase. Repairs were analyzed in terms of incomplete words, revisions, and repetitions. If a target word or segment was annotated as a repair, it may have been caused by the corresponding source text word or segment or the source text word or segment that was about to be sight translated. Two types of (arbitrary) symbols were used to annotate repairs in oral transcriptions: the question mark for incomplete words and a pair of ampersands for revisions and repetitions. Repairs were marked as being either major or minor.

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Errors were categorized as being related to meaning or expression (Agrifoglio 2004; Lee 2012). Meaning errors were comprehension failures of the source text, and thus, meaning errors were considered source-text oriented. Expression errors were rendition problems in the target text, such as grammar and pronunciation mistakes, and an inappropriate or inaccurate use of words and collocations in the target text language. Expression errors were thus target-text oriented. Omissions referred to the lack of the target text correspondence to the source text (Napier 2015). Omissions occurred when the translation of a source text word was completely absent, or the translation of certain aspects or nuances of a source text word were absent. Errors and omissions were also labeled as being major or minor. If the expression error (such as a grammatical mistake) did not affect the correct understanding of the meaning, it was considered a minor expression error (for example, “a” in “a open world” was considered a minor expression error). If the expression error caused difficulties in comprehension or the incorrect understanding of the meaning, it was then considered to be a major error. If the omission resulted in the loss of essential information, it was considered a major one. If the omission did not affect the conveyance of the essential meaning, it was then considered a minor one.

4.3.8 Data Analysis for Local Style 3 Finally, I examined the third dimension of local translation styles, i.e., how translation problems affect the reading-speech coordination in actual sight translation. The coordination behaviors were measured by the Max. and Min. EVS at the word level, which were obtained based on the data analysis of global styles as described in Sect. 4.3.5. Here, the translation problem was the source text word that met the following two criteria. First, it had to have been among the top 15 words with the longest TFD in actual sight translation for the same participant. Second, it had to have been among the top 15 words with the longest TFD in actual sight translation for at least four of the total 13 novices, or for at least three of the total nine professionals. Thus, the translation problem was the source text word that received relatively high TFDs in actual sight translation. Furthermore, it was termed an actual problem because it occurred in the stage of actual translation (see Angelone 2018). Moreover, since these translation problems attracted relatively high TFDs for most participants within each group, they were deemed to be common actual problems. Before conducting the inferential analysis of the problem effect on the EVS, the distribution of Max. and Min. EVS was plotted using the sm.density.compare function from the sm package (Bowman and Azzalini 2018). Following on from this, an LMER analysis was performed to investigate the effect of actual translation problems on the coordination behaviors of each group in actual sight translation. The dependent variables were Max. and Min. EVS at word level, and the test predictor was AOI with two levels (common actual problem [CAP] versus common actual non-problem [CANP]). The task time each participant spent during

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the preparatory reading was entered as the control predictor in the LMER model. To examine whether the effect of actual problems differed between novices and professionals, I selected the common actual problems for both groups (CAPFBG) and common actual non-problems for both groups (CANPFBG) for further analysis. As a result, the LMER model consisted of group, AOI (CAPFBG vs. CANPFBG) and their interaction as the test predictors, and the task time spent in preparation as the control predictor. Apart from conducting the inferential analysis of the problem effect on the EVS, it was important to probe into “‘what goes on in between the first and the last fixation on a data point before the onset of output production” as suggested by Timarová et al. (2011, p. 135). Thus, bubble graphs from Excel were used to illustrate what happened during the EVS of a specific translation problem.

4.4 Summary This chapter has provided detailed information on the indicators for each research question, how the experiment of sight translation was conducted, how the eye data and oral renditions were collected, and how the collected data was analyzed in light of each research question.

Appendix Experimental Stimuli and Reference Translations. *Slash represents word segmentation of each text. Political words with Chinese features are in bold (date retrieved on July 15, 2019). Traditional words were underlined. The rest are ordinary words. The reference translations are selected from Xi Jinping: The Governance of China. Text 1

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Translations of Text 1 Pass on the torch of peace from generation to generation and ensure civilization flourishes. China stands for building a community of shared future for mankind and achieving inclusive and win-win development. Great visions can be realized only through actions. To achieve this goal, the international community should promote partnership, growth, inter-civilization exchanges, and the building of sound ecosystems. We should build a world of lasting peace through dialogue and consultation. When countries enjoy peace, so will the world; when countries fight, the world suffers. We should build a world of common prosperity through win-win cooperation. Instead of beggaring their neighbors, countries should stick together like passengers in the same boat. We should build an open and inclusive world through exchanges and mutual learning. Diverse civilizations should draw on each other to achieve common progress. We should make our world clean and beautiful by pursuing green and lowcarbon development. Clear waters and green mountains are as good as mountains of gold and silver. We should pursue a circular and sustainable way of life and work. Text 2

Translations of Text 2 In 2013, I proposed building the Silk Road Economic Belt and the twenty-first Century Maritime Silk Road, which is now known as the Belt and Road Initiative. As a Chinese saying goes, “Peaches and plums do not speak, but they are so attractive that a path is formed below the trees.” Countries have become involved in this initiative. The Belt and Road Initiative is becoming a reality. These four years have seen deeper policy coordination. The Belt and Road Initiative is not meant to reinvent the wheel. Rather, it aims to leverage the comparative strengths of the countries involved and coordinate their development strategies. These four years have seen enhanced infrastructure connectivity. Building roads and railways helps create prosperity in all sectors. These four years have seen increased people-to-people contacts. Friendship, which derives from close contacts between peoples, holds the key to sound stateto-state relations. We countries participating in the Belt and Road Initiative have pooled our efforts to build the educational Silk Road and the health Silk Road. Our cooperation has helped lay a solid popular foundation. We should build on the sound momentum and steer the Belt and Road Initiative toward greater success.

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Text 3

Translations of Text 3 On the basis of a thorough understanding of the people’s aspirations for a better life, we will strive for the Chinese Dream of national rejuvenation. In enforcing strict Party discipline, we have focused on resolving problems which posed the most serious threats to the Party’s governing status. In four decades since the start of reform and opening up, China’s productive forces have developed rapidly. The ongoing successes of Chinese socialism signify that the Chinese, who went through untold hardships, have made the leaps from liberation to prosperity and thence to a strong nation. This means that socialism has flourished in China, and that China is contributing its wisdom to the problems facing mankind. We have made a pledge to the people that China will complete a moderately prosperous society in all respects by 2020, which is the first of the Two Centenary Goals. Text 4

Translations of Text 4 As a line in an old Chinese poem goes, “Honey melons hang on bitter vines; sweet dates grow on thistles and thorns.” Nothing is perfect in the world. Economic globalization has created new problems, but this is no justification to write it off altogether. Rather, we should adapt to and guide economic globalization. We should develop a dynamic, innovation-driven growth model. The fundamental issue plaguing the global economy is the lack of driving force for growth. Innovation is the primary force leading development. We should seize opportunities presented by the new round of industrial revolution and the digital economy. We should meet the challenges of

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climate change and aging population. We should also address the negative impact of IT and automation on jobs. We Chinese applaud the achievements of others. We are not jealous of others’ success. We welcome them aboard the express train of China’s development.

References Agrifoglio, M. (2004). Sight translation and interpreting: A comparative analysis of constraints and failures. Interpreting, 6(1), 43–67. https://doi.org/10.1075/intp.6.1.05agr. Angelone, E. (2018). Reconceptualizing problems in translation using triangulated process and product data. In I. Lacruz & R. Jääskeläinen (Eds.), Innovation and expansion in translation process research (pp. 17–36). Amsterdam/Philadelphia: John Benjamins Publishing Company. Baayen, H. (2008). Analyzing linguistic data: A Practical introduction to statistics using R. Cambridge: Cambridge University Press. Baayen, R. H., & Milin, P. (2010). Analyzing reaction times. International Journal of Psychological Research, 3(2), 12–28. https://doi.org/10.21500/20112084.807. Balling, L., Hvelplund, K., & Sjørup, A. (2014). Evidence of parallel processing during translation. Meta, 59(2), 234–259. https://doi.org/10.7202/1027474ar. Barr, D. J., Levy, R., Scheepers, C., & Tily, H. J. (2013). Random effects structure for confirmatory hypothesis testing: Keep it maximal. Journal of Memory and Language, 68(3), 255–278. https:// doi.org/10.1016/j.jml.2012.11.001. Bates, D., Kliegl, R., Vasishth, S., & Baayen, H. (2018). Parsimonious mixed models. arXiv:1506. 04967v2[stat.ME]. Bates, D., Maechler, M., Bolker, B., & Walker, S. (2015). Fitting linear mixed-effects models using LMER4. Journal of Statistical Software, 67(1), 1–48. https://doi.org/10.18637/jss.v067.i01. Bowman, A., & Azzalini, A. (2018). Package ‘SM’ [R package]. Retrieved from https://cran.r-pro ject.org/web/packages/sm/index.html. Carl, M. (2008). Framework of a probabilistic gaze mapping model for reading. In S. Göpferich, A. L. Jakobsen, & I. M. Mees (Eds.), Looking at eyes: Eye-tracking studies of reading and translation processing (pp. 193–202). Frederiksberg: Samfundslitteratur. Dragsted, B. (2005). Segmentation in translation: Differences across levels of expertise and difficulty. Target, 17(1), 49–70. https://doi.org/10.1075/target.17.1.04dra. García, A. M., Ibáñez, A., Huepe, D., Houck, A. L., Michon, M., Lezama, C. G., et al. (2014). Word reading and translation in bilinguals: the impact of formal and informal translation expertise. Frontiers in Psychology, 5, 1302. https://doi.org/10.3389/fpsyg.2014.01302. Holmqvist, K., Nyström, M., Andersson, R., Dewhurst, R., Jarodzka, H., & Van de Weijer, J. (2011). Eye tracking: A comprehensive guide to methods and measures. Oxford: Oxford University Press. Hvelplund, K. T. (2014). Eye tracking and the translation process: Reflections on the analysis and interpretation of eye-tracking data. In R. Muñoz Martín (Ed.), Minding translation, Special issue of MonTI, 1(1), 201–223. Ivanova, A. (2000). The use of retrospection in research on simultaneous interpreting. In S. Tirkkonen-Condit & R. Jääskeläinen (Eds.), Tapping and mapping the processes of translation and interpreting: Outlooks on empirical research (pp. 27–52). Amsterdam/Philadelphia: John Benjamins Publishing Company. Krings, H. P. (1986). Translation problems and translation strategies of advanced German learners of French (L2). In J. House & S. Blum-Kulka (Eds.), Interlingual and intercultural communication: Discourse and cognition in translation and second language acquisition studies (pp. 263–276). Tübingen: Gunter Narr Verlag. Kuznetsova, A., Brockhoff, P., & Christensen, R. H. B. (2019). Package ‘lmertest’ [R package]. Retrieved from https://cran.r-project.org/web/packages/lmerTest/index.html.

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Lee, J. (2012). What skills do student interpreters need to learn in sight translation training? Meta, 57(3), 694–714. https://doi.org/10.7202/1017087ar. Lenth, R., Singmann, H., Love, J., Buerkner, P., Herve, M. (2019). Package ‘emmeans’ [R package]. Retrieved from https://cran.r-project.org/web/packages/emmeans/index.html, https://doi.org/10. 1080/00031305.1980.10483031. Lörscher, W. (1991). Translation performance, translation process, and translation strategies: A psycholinguistic investigation. Tübingen: Gunter Narr Verlag. Napier, J. (2015). Omission. In F. Pöchhacker (Ed.), Routledge encyclopedia of interpreting studies (pp. 289–291). London and New York: Routledge. R Core Team. (2018). A language and environment for statistical computing. Vienna, Austria: R Foundation for Statistical Computing. Shreve, G. M., Lacruz, I., & Angelone, E. (2011). Sight translation and speech disfluency: Performance analysis as a window to cognitive translation processes. In C. Alvstad, A. Hild, & E. Tiselius (Eds.), Methods and strategies of process research: Integrative approaches in translation studies (pp. 93–120). Amsterdam/Philadelphia: John Benjamins Publishing Company. Timarová, Š., Dragsted, B., & Hansen, I. G. (2011). Time lag in translation and interpreting: A methodological exploration. In C. Alvstad, A. Hild, & E. Tiselius (Eds.), Methods and strategies of process research (pp. 121–146). Amsterdam/Philadelphia: John Benjamins Publishing Company. Tobii Pro. (2017). Tobii studio user’s manual (version 3.4.8). Sweden: Tobii AB. Tremblay, A., & Ransijn, J. (2015). Package ‘LMERConvenienceFunctions’ [R package]. Retrieved from https://cran.r-project.org/web/packages/LMERConvenienceFunctions/index.html. Xi, J. (2017). Xi Jinping: The Governance of China II. Beijing: Foreign Language Press. [习近平. 2017.《习近平谈治国理政》 (第二卷). 北京:外文出版社.].

Chapter 5

Global and Local Styles of Sight Translation

Abstract This chapter presents the descriptive data and the LMER results for each of the six research questions. Qualitative analyses were also conducted to illustrate the differences between, and implications of, the behavioral styles. I shall first present the results of global translation styles, namely eye-movement behaviors as reflected by the five global measures in the two stages in Sect. 5.1, interaction between gaze behaviors in preparation and gaze behaviors in subsequent actual sight translation in Sect. 5.2, and behavioral patterns of reading-speech coordination at textual level in Sect. 5.3. Following on from this, the results of local translation styles will be reported on, namely problem identification behaviors in Sect. 5.4, problem-solving behaviors in Sect. 5.5, and the effect of actual translation problems on reading-speech coordination in Sect. 5.6. Keywords Gaze behaviors in preparation · Gaze behaviors in actual sight translation · Reading-speech coordination

5.1 Eye-Movement Behaviors The first research question to be answered was: how are the eye-movement behaviors affected by the two different stages of sight translation? Do novice and professional interpreters exhibit different gaze behaviors in each of the two stages? In this section, I shall attempt to answer this question by presenting the overall statistics of the gaze behaviors, and how they differed between each interpreter group, in each of the two stages. Following that, the LMER results of each of the five global measures will be reported.

5.1.1 Overall Gaze Patterns In order to examine the global, textual behaviors in preparation and in actual sight translation, this study used five global measures, of which time was one, and eye © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2020 W. Su, Eye-Tracking Processes and Styles in Sight Translation, New Frontiers in Translation Studies, https://doi.org/10.1007/978-981-15-5675-3_5

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Table 5.1 Means and standard deviations for time and the eye measures in preparation and actual sight translation by each participant Measures/stages

Stage 1: preparation

Stage 2: actual sight translation

Mean

5.96

2.15

SD

2.76

0.48

FC

Mean

1,014.42

325.53

SD

506.83

73.1

SA (°)

Mean

3.22

2.77

SD

0.51

0.23

Mean

272.1

314

SD

45.23

57.52

Mean

3

3.15

SD

0.29

0.33

TT (min)

FD (ms) PD (mm)

SD inter-stage variation

measures comprised the other four. One reason for using various indicators was to be able to triangulate different measures. Another reason was that each indicator had their own characteristic and strength. First, the descriptive statistics for time and the four eye measures in each of the two stages were presented. As shown in Table 5.1, each participant spent 5.96 min pre-reading each source text of 112 Chinese words in preparation, with an average pre-reading speed of 19 Chinese words per minute. Each spent 2.15 min reading and sight translating each text in the subsequent actual sight translation, with a mean pre-reading speed of 52 Chinese words per minute. Overall, participants spent more time, produced a higher FC, and larger SA, in preparation than in actual sight translation. However, the FD was shorter, and the PD was smaller during preparatory reading than reading in actual sight translation. The descriptive data for each of the five measures between novices and professionals was also summarized. As shown in Table 5.2, each novice interpreter spent 4.84 min across the two stages while each professional interpreter spent only 2.91 min. The overall speed of professionals was found to have been faster. Moreover, novices produced a larger FC than professionals across the stages. The SA, FD, and PD were similar between the two groups. A series of LMER analyses were performed to further examine whether the influence of interpreting experience on time and the other eye measures varied across the two stages.

5.1.2 Task Time Task time (TT) was the first of the five global measures used for the investigation of global translation styles. Table 5.3 presents the average time each group spent on each of the two stages. The average TT of novices decreased by 5.39 min (7.54 − 2.15)

5.1 Eye-Movement Behaviors

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Table 5.2 Means and standard deviations for time and the eye measures between novices and professionals across the two stages Measures/Groups

Novice

TT (min)

Professional

Mean

4.84

SD

1.25

2.91 0.62

FC

Mean

806.82

472.32

SD

252.88

101.03

SA (°)

Mean

3.13

3.06

SD

0.52

0.28

Mean

276.97

295.39

SD

216.39

247.27

Mean

3.09

2.93

SD

0.26

0.37

FD (ms) PD (mm) SD inter-participant variation

Table 5.3 Means for TT (min) of each group in each stage Group

Stage Stage 1: preparation

Stage 2: actual sight translation

Novice

7.54

2.15

Professional

3.69

2.14

from preparation to actual sight translation, while the average TT of professionals decreased by a less significant 1.55 min (3.69 − 2.14). Furthermore, the difference in time between the two groups was much more obvious in preparation than in actual sight translation, with a difference of 3.85 in preparation (7.54 − 3.69) but only 0.01 in actual sight translation (2.15 − 2.14). The descriptive data seems to show an interaction effect between stage and group on TT. The LMER results of the TT model (presented in Table 5.4) indeed corroborate the descriptive data. Table 5.4 LMER results of TT model Fixed effects

Estimate

SE

Intercept

12.156

0.072

Stage 2

−0.84

0.086

Professional

−0.344

0.088

0.656

0.172

Stage 2: professional

d.f.

t

p

6.516

168.330