A decoder for syntax-based statistical MT

Kenji Yamada, Kevin Knight
2001 Proceedings of the 40th Annual Meeting on Association for Computational Linguistics - ACL '02  
This paper describes a decoding algorithm for a syntax-based translation model (Yamada and Knight, 2001) . The model has been extended to incorporate phrasal translations as presented here. In contrast to a conventional word-to-word statistical model, a decoder for the syntaxbased model builds up an English parse tree given a sentence in a foreign language. As the model size becomes huge in a practical setting, and the decoder considers multiple syntactic structures for each word alignment,
more » ... ral pruning techniques are necessary. We tested our decoder in a Chinese-to-English translation system, and obtained better results than IBM Model 4. We also discuss issues concerning the relation between this decoder and a language model. . These models are automatically trained using monolingual (for the LM) and bilingual (for the TM) corpora. A decoder then finds the best English sentence given a foreign sentence that maximizes P¤ ¥ £ ¢ ¦
doi:10.3115/1073083.1073134 dblp:conf/acl/YamadaK02 fatcat:pld5iqqefvgkpcbohjmym6ncfy