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

Masaki Murata, Kiyotaka Uchimoto, Qing Ma, Hitoshi Isahara

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.