Statistical machine translation based on hierarchical phrase alignment (2002)
| Venue: | Proc. of the 9th Intl. Conference on Theoretical and Methodological Issues in Machine Translation |
| Citations: | 5 - 0 self |
BibTeX
@INPROCEEDINGS{Watanabe02statisticalmachine,
author = {Taro Watanabe and Kenji Imamura and Eiichiro Sumita},
title = {Statistical machine translation based on hierarchical phrase alignment},
booktitle = {Proc. of the 9th Intl. Conference on Theoretical and Methodological Issues in Machine Translation},
year = {2002},
pages = {188--198}
}
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Abstract
This paper describes statistical machine translation improved by applying hierarchical phrase alignment. The hierarchical phrase alignment is a method to align bilingual sentences phrase-by-phrase employing the partial parse results. Based on the hierarchical phrase alignment, a translation model is trained on a chunked corpus by converting hierarchically aligned phrases into a sequence of chunks. The second method transforms the bilingual correspondence of the phrase alignments into that of translation model. Both of our approaches yield better quality of the translaiton model. 1
