research-article

Recognition of translator expertise using sequences of fixations and keystrokes

Authors:

Pascual Martínez-Gómez,

Akiko AizawaAuthors Info & Claims

ETRA '14: Proceedings of the Symposium on Eye Tracking Research and Applications

Pages 299 - 302

https://doi.org/10.1145/2578153.2578201

Published: 26 March 2014 Publication History

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Abstract

Professional human translation is necessary to meet high quality standards in industry and governmental agencies. Translators engage in multiple activities during their task, and there is a need to model their behavior, with the objective to understand and optimize the translation process. In recent years, user interfaces enabled us to record user events such as eye-movements or keystrokes. Although there have been insightful descriptive analysis of the translation process, there are multiple advantages in enabling quantitative inference. We present methods to classify sequences of fixations and keystrokes into activities and model translation sessions with the objective to recognize translator expertise. We show significant error reductions in the task of recognizing certified translators and their years of experience, and analyze the characterizing patterns.

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Cited By

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Lu SCarl MYao XSu W(2020)Predicting translation behaviorsby using Hidden Markov ModelTranslation, Cognition & BehaviorTranslation, Cognition and Behavior10.1075/tcb.00035.lu3:1(76-99)Online publication date: 13-May-2020
https://doi.org/10.1075/tcb.00035.lu
Hatzidaki A(2019)Using experimental approaches to study translationTranslation, Cognition & BehaviorTranslation, Cognition and Behavior10.1075/tcb.00018.hat2:1(35-54)Online publication date: 7-Mar-2019
https://doi.org/10.1075/tcb.00018.hat
Schaeffer MNitzke JHansen-Schirra S(2019)Predictive Turn in Translation Studies: Review and ProspectsHandbook of the Changing World Language Map10.1007/978-3-319-73400-2_217-1(1-23)Online publication date: 21-Apr-2019
https://doi.org/10.1007/978-3-319-73400-2_217-1
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Index Terms

Recognition of translator expertise using sequences of fixations and keystrokes
1. Computing methodologies
  1. Artificial intelligence
    1. Philosophical/theoretical foundations of artificial intelligence
      1. Cognitive science
2. Human-centered computing
  1. Human computer interaction (HCI)

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Published In

ETRA '14: Proceedings of the Symposium on Eye Tracking Research and Applications

March 2014

394 pages

ISBN:9781450327510

DOI:10.1145/2578153

Conference Chairs:
Pernilla Qvarfordt
FX Palo Alto Laboratory
,
Dan Witzner Hansen
IT University, Denmark

Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author.

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Association for Computing Machinery

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Published: 26 March 2014

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ETRA '14

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ETRA '14: Eye Tracking Research and Applications

March 26 - 28, 2014

Florida, Safety Harbor

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Overall Acceptance Rate 69 of 137 submissions, 50%

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Lu SCarl MYao XSu W(2020)Predicting translation behaviorsby using Hidden Markov ModelTranslation, Cognition & BehaviorTranslation, Cognition and Behavior10.1075/tcb.00035.lu3:1(76-99)Online publication date: 13-May-2020
https://doi.org/10.1075/tcb.00035.lu
Hatzidaki A(2019)Using experimental approaches to study translationTranslation, Cognition & BehaviorTranslation, Cognition and Behavior10.1075/tcb.00018.hat2:1(35-54)Online publication date: 7-Mar-2019
https://doi.org/10.1075/tcb.00018.hat
Schaeffer MNitzke JHansen-Schirra S(2019)Predictive Turn in Translation Studies: Review and ProspectsHandbook of the Changing World Language Map10.1007/978-3-319-73400-2_217-1(1-23)Online publication date: 21-Apr-2019
https://doi.org/10.1007/978-3-319-73400-2_217-1
Schaeffer MNitzke JHansen-Schirra S(2019)Predictive Turn in Translation Studies: Review and ProspectsHandbook of the Changing World Language Map10.1007/978-3-030-02438-3_217(3939-3961)Online publication date: 23-Oct-2019
https://doi.org/10.1007/978-3-030-02438-3_217
Carl MSchaeffer M(2018)Outline for a Relevance Theoretical Model of Machine Translation Post-editingResearching Cognitive Processes of Translation10.1007/978-981-13-1984-6_3(49-67)Online publication date: 27-Oct-2018
https://doi.org/10.1007/978-981-13-1984-6_3
Hvelplund K(2017)Eye Tracking in Translation Process ResearchThe Handbook of Translation and Cognition10.1002/9781119241485.ch14(248-264)Online publication date: 18-Feb-2017
https://doi.org/10.1002/9781119241485.ch14
Carl MBangalore SSchaeffer M(2016)Computational linguistics and translation studiesBorder Crossings10.1075/btl.126.11car(225-244)Online publication date: 30-Aug-2016
https://doi.org/10.1075/btl.126.11car
Läubli SGermann U(2016)Statistical Modelling and Automatic Tagging of Human Translation ProcessesNew Directions in Empirical Translation Process Research10.1007/978-3-319-20358-4_8(155-181)Online publication date: 2016
https://doi.org/10.1007/978-3-319-20358-4_8

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A product and process analysis of post-editor corrections on neural, statistical and rule-based machine translation output

Towards achieving a delicate blending between rule-based translator and neural machine translator

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