Combining quality prediction and system selection for improved automatic translation output

Authors:
Radu Soricut;Sushant Narsale
Affiliations:
SDL Language Weaver, Los Angeles, CA;Google Inc., Mountain View, CA
Venue:
WMT '12 Proceedings of the Seventh Workshop on Statistical Machine Translation
Year:
2012

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Abstract

This paper presents techniques for referencefree, automatic prediction of Machine Translation output quality at both sentence- and document-level. In addition to helping with document-level quality estimation, sentence-level predictions are used for system selection, improving the quality of the output translations. We present three system selection techniques and perform evaluations that quantify the gains across multiple domains and language pairs.