Continuous adaptation to user feedback for statistical machine translation
Abstract
This paper gives a detailed experiment feedback of different approaches to adapt a statistical machine translation system towards a targeted translation project, using only small amounts of parallel in-domain data. The experiments were performed by professional translators under realistic conditions of work using a computer assisted translation tool. We analyze the influence of these adaptations on the translator productivity and on the overall post-editing effort. We show that significant improvements can be obtained by using the presented adaptation techniques.Citation
Blain, F., Bougares, F., Hazem, A., Barrault, L. and Schwenk, H. (2015) Continuous adaptation to user feedback for statistical machine translation, Proceedings of the 2015 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, May 31 – June 5, 2015, Denver, Colorado.Additional Links
https://www.aclweb.org/anthology/N15-1103/Type
Conference contributionLanguage
enDescription
© 2015 The Authors. Published by Association for Computational Linguistics . This is an open access article available under a Creative Commons licence. The published version can be accessed at the following link on the publisher’s website: https://www.aclweb.org/anthology/N15-1103ISBN
9781941643495Scopus Count
Except where otherwise noted, this item's license is described as https://creativecommons.org/licenses/by-nc-sa/4.0/