Su Wenchao | Guangdong University of Foreign Studies
The translation process can be studied as sequences of activity units. The application of machine learning
technology offers researchers new possibilities in the study of the translation process. This research project developed a
program, activity unit predictor, using the Hidden Markov Model. The program takes in duration, translation phase, target
language and fixation as the input and produces an activity unit type as the output. The highest prediction accuracy reached is
61%. As one of the first endeavors, the program demonstrates strong potential of applying machine learning in translation process
research.
2014 “Sub-sentence Level Analysis of Machine Translation Post-editing Effort.” In Post-editing of Machine Translation: Processes and applications. Edited by S. O’Brien, L. W. Balling, M. Carl, M. Simard and L. Specia, 170–199. Newcastle: Cambridge Scholars.
Bahdanau, Dzmitry, Kyunghyun Cho, and Yoshua Bengio
2015 “Neural Machine Translation by Jointly Learning to Align and Translate.” Paper presented at International Conference on Learning Representations (San Diego, USA, 7–9 May 2015).
Bangalore, Srinivas, Bergljot Behrens, Michael Carl, Maheshwar Ghankot, Arndt Heilmann, Jean Nitzke, Moritz J. Schaeffer, and Annegret Sturm
2016 “Syntactic Variance and Priming Effects in Translation.” In New Directions in Empirical Translation Process Research. Edited by M. Carl, S. Bangalore and M. Schaeffer, 211–238. Cham: Springer International.
Campbell, Stuart
2000 “Choice Network Analysis in Translation Research.” In Intercultural faultlines: Research models in translations studies. Edited by M. Olohan, 29–42. Manchester: St. Jerome.
Carl, Michael and Arnt Lykke Jakobsen
2009 “Towards Statistical Modelling of Translators’ Activity Data.” International Journal of Speech Technology 121: 125–138.
Carl, Michael and Moritz J. Schaeffer
2017 “Sketch of a Noisy Channel Model for the Translation Process.” In Empirical modelling of translation and interpreting. Edited by S. Hansen-Schirra, O. Czulo, and S. Hofmann, 71–116. Berlin: Language Science Press.
Carl, Michael, Srinivas Bangalore and Moritz J. Schaeffer
2016a “Introduction and Overview.” In New Directions in Empirical Translation Process Research. Edited by M. Carl, S. Bangalore and M. Schaeffer, 3–12. Cham: Springer International.
Carl, Michael, Srinivas Bangalore and Moritz J. Schaeffer
2016b “The CRITT Translation Process Research Database.” In New Directions in Empirical Translation Process Research. Edited by M. Carl, S. Bangalore and M. Schaeffer, 13–54. Cham: Springer International.
Heilmann, Arndt and Stella Neumanm
2016 “Dynamic Pause Assessment of Keystroke Logged Data for the Detection of Complexity in Translation and Monolingual Text Production.” Paper presented at Workshop on Computational Linguistics for Linguistic Complexity (Osaka, Japan, 11–17 December 2016).
Lacruz, Isabel and Gregory Shreve
2014 “Pauses and Cognitive Effort in Post-Editing.” In Post-editing of Machine Translation: Processes and applications. Edited by S. O’Brienet al., 246–273. Newcastle: Cambridge Scholars.
Läubli, Samuel and Ulrich Germann
2016 “Statistical Modelling and Automatic Tagging of Human Translation Processes.” In New Directions in Empirical Translation Process Research. Edited by M. Carl, S. Bangalore and M. Schaeffer, 155–181. Cham: Springer International.
Martínez Gómez, Pascual Akshay Minocha, Jin Huang, Michael Carl, Srinivas Bangalore, and Akiko Aizawa
2014 “Recognition of Translator Expertise using Sequences of Fixations and Keystrokes.” Paper presented at Eye Tracking Research and Applications Symposium (Safety Habor, USA, 26–28 March 2014).
Minh, Volodymyret al.
2014 “Recurrent Models of Visual Attention.” Paper presented at Neural Information Processing Systems (Montreal, 8–13 December 2014).
2024. Hesitation, orientation, and flow: A taxonomy for deep temporal translation architectures. Ampersand► pp. 100164 ff.
Su, Wenchao
2020. Issues and Approaches to CTIS. In Eye-Tracking Processes and Styles in Sight Translation [New Frontiers in Translation Studies, ], ► pp. 9 ff.
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