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.
@article{arxiv.cs/0112003,
title = {Using a Support-Vector Machine for Japanese-to-English Translation of Tense, Aspect, and Modality},
author = {Masaki Murata and Kiyotaka Uchimoto and Qing Ma and Hitoshi Isahara},
journal= {arXiv preprint arXiv:cs/0112003},
year = {2007}
}