Paper: Phrasal Segmentation Models for Statistical Machine Translation

ACL ID C08-2005
Title Phrasal Segmentation Models for Statistical Machine Translation
Venue International Conference on Computational Linguistics
Session Poster Session
Year 2008
Authors

Phrasal segmentation models define a mapping from the words of a sentence to sequences of translatable phrases. We discuss the estimation of these models from large quantities of monolingual train- ing text and describe their realization as weighted finite state transducers for incor- poration into phrase-based statistical ma- chine translation systems. Results are re- ported on the NIST Arabic-English trans- lation tasks showing significant comple- mentary gains in BLEU score with large 5-gram and 6-gram language models.