Using a Support-Vector Machine for Japanese-to-English Translation of Tense, Aspect, and Modality

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Dec 05, 2001
Masaki Murata, Kiyotaka Uchimoto, Qing Ma, Hitoshi Isahara
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This paper describes experiments carried out using a variety of machine-learning methods, including the k-nearest neighborhood method that was used in a previous study, for the translation of tense, aspect, and modality. It was found that the support-vector machine method was the most precise of all the methods tested.

* ACL Workshop, the Data-Driven Machine Translation, 2001  * 8 pages. Computation and Language  
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