Abstract
Advanced translation workbenches with detailed logging and eye-tracking capabilities greatly facilitate the recording of key strokes, mouse activity, or eye movement of translators and post-editors. The large-scale analysis of the resulting data logs, however, is still an open problem. In this chapter, we present and evaluate a statistical method to segment raw keylogging and eye-tracking data into distinct Human Translation Processes (HTPs), i.e., phases of specific human translation behavior, such as orientation, revision, or pause. We evaluate the performance of this automatic method against manual annotation by human experts with a background in Translation Process Research
Original language | English |
---|---|
Title of host publication | New Directions in Empirical Translation Process Research |
Subtitle of host publication | Exploring the CRITT TPR-DB |
Publisher | Springer |
Pages | 155-181 |
Number of pages | 27 |
ISBN (Electronic) | 978-3-319-20358-4 |
ISBN (Print) | 978-3-319-20357-7 |
DOIs | |
Publication status | Published - 2016 |
Publication series
Name | New Frontiers in Translation Studies |
---|---|
Publisher | Springer International Publishing |
ISSN (Print) | 2197-8689 |
ISSN (Electronic) | 2197-8697 |
Fingerprint
Dive into the research topics of 'Statistical Modelling and Automatic Tagging of Human Translation Processes'. Together they form a unique fingerprint.Profiles
-
Ulrich Germann
- School of Informatics - Senior Computing Officer (Research)
- Institute of Language, Cognition and Computation
- Language, Interaction, and Robotics
Person: Academic: Research Active (Research Assistant)