Skip to main content

Research Repository

Advanced Search

Recognition of Translator Expertise Using Sequences of Fixations and Keystrokes

Martinez-Gomez, P.; Minocha, A.; Huang, J.; Carl, M.; Bangalore, S.; Aizawa, A.

Authors

P. Martinez-Gomez

A. Minocha

M. Carl

S. Bangalore

A. Aizawa



Contributors

Pernilla Qvarfordt
Editor

Dan Witzner Hansen
Editor

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.

Citation

Martinez-Gomez, P., Minocha, A., Huang, J., Carl, M., Bangalore, S., & Aizawa, A. (2014). Recognition of Translator Expertise Using Sequences of Fixations and Keystrokes. In P. Qvarfordt, & D. Witzner Hansen (Eds.), Proceedings of the Symposium on Eye Tracking Research and Applications - ETRA '14 (299-302). https://doi.org/10.1145/2578153.2578201

Conference Name ETRA '14 Symposium on Eye Tracking Research and Applications.
Conference Location Florida, USA
Online Publication Date Mar 26, 2014
Publication Date 2014-03
Deposit Date Oct 3, 2014
Publisher Association for Computing Machinery (ACM)
Pages 299-302
Book Title Proceedings of the Symposium on Eye Tracking Research and Applications - ETRA '14
DOI https://doi.org/10.1145/2578153.2578201
Public URL https://durham-repository.worktribe.com/output/1155513