Using paraphrases for parameter tuning in statistical machine translation

TitleUsing paraphrases for parameter tuning in statistical machine translation
Publication TypeConference Papers
Year of Publication2007
AuthorsMadnani N, Ayan N F, Resnik P, Dorr BJ
Conference NameProceedings of the Second Workshop on Statistical Machine Translation
Date Published2007///
PublisherAssociation for Computational Linguistics
Conference LocationStroudsburg, PA, USA

Most state-of-the-art statistical machine translation systems use log-linear models, which are defined in terms of hypothesis features and weights for those features. It is standard to tune the feature weights in order to maximize a translation quality metric, using held-out test sentences and their corresponding reference translations. However, obtaining reference translations is expensive. In this paper, we introduce a new full-sentence paraphrase technique, based on English-to-English decoding with an MT system, and we demonstrate that the resulting paraphrases can be used to drastically reduce the number of human reference translations needed for parameter tuning, without a significant decrease in translation quality.