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

2001/12/05 by Masaki Murata, Kiyotaka Uchimoto, Qing Ma +1
Computer Science · #cs.CL

paper · pdf

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

arxiv created 2001/12/05 · arxiv updated 2009/11/30

Abstract

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.

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