Martins, André FT
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AbstractWe report the results of the WMT20 shared task on Quality Estimation, where the challenge is to predict the quality of the output of neural machine translation systems at the word, sentence and document levels. This edition included new data with open domain texts, direct assessment annotations, and multiple language pairs: English-German, English-Chinese, Russian-English, Romanian-English, Estonian-English, Sinhala-English and Nepali-English data for the sentence-level subtasks, English-German and English-Chinese for the word-level subtask, and English-French data for the document-level subtask. In addition, we made neural machine translation models available to participants. 19 participating teams from 27 institutions submitted altogether 1374 systems to different task variants and language pairs.
CitationSpecia, L., Blain, F., Fomicheva, M. et al. (2020) Findings of the WMT 2020 shared task on quality estimation, Proceedings of the Fifth Conference on Machine Translation, November 2020, pp. 743–764.
Description© 2020 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/2020.wmt-1.79
Except where otherwise noted, this item's license is described as https://creativecommons.org/licenses/by/4.0/