Affiliation:
1. Renmin University of China
2. Kent State University
3. Guangdong University of Foreign Studies
Abstract
Abstract
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.
Publisher
John Benjamins Publishing Company
Subject
Linguistics and Language,Language and Linguistics,Communication
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4. Towards statistical modelling of translators’ activity data
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