2017 •
Producing Unseen Morphological Variants in Statistical Machine Translation
Authors:
Matthias Huck, Aleš Tamchyna, Ondrej Bojar, Alexander Fraser
Abstract:
Translating into morphologically rich languages is difficult. Although the coverage of lemmas may be reasonable, many morphological variants cannot be learned from the training data. We present a statistical translation system that is able to produce these inflected word forms. Different from most previous work, we do not separate morphological prediction from lexical choice into two consecutive steps. Our approach is novel in that it is integrated in decoding and takes advantage of context information from both the source language and the targ (...)
Translating into morphologically rich languages is difficult. Although the coverage of lemmas may be reasonable, many morphological variants cannot be learned from the training data. We present a statistical translation system that is able to produce these inflected word forms. Different from most previous work, we do not separate morphological prediction from lexical choice into two consecutive steps. Our approach is novel in that it is integrated in decoding and takes advantage of context information from both the source language and the target language sides. (Read More)
Matthias Huck, Aleš Tamchyna, Ondřej Bojar, Alexander Fraser
Proceedings of the 15th Conference of the European Chapter of the Association for Computational Ling (...) ·
2017
Natural language processing |
Artificial intelligence |
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