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- Title
Japanese-to-English translations of tense, aspect, and modality using machine-learning methods and comparison with machine-translation systems on market.
- Authors
Murata, Masaki; Qing Ma; Uchimoto, Kiyotaka; Kanamaru, Toshiyuki; Isahara, Hitoshi
- Abstract
This paper describes experiments carried out utilizing a variety of machine-learning methods (the k-nearest neighborhood, decision list, maximum entropy, and support vector machine), and using six machine-translation (MT) systems available on the market for translating tense, aspect, and modality. We found that all these, including the simple string-matching-based k-nearest neighborhood used in a previous study, obtained higher accuracy rates than the MT systems currently available on the market. We also found that the support vector machine obtained the best accuracy rates (98.8%) of these methods. Finally, we analyzed errors against the machine-learning methods and commercially available MT systems and obtained error patterns that should be useful for making future improvements.
- Subjects
LANGUAGE &; languages; TRANSLATIONS; TRANSLATING &; interpreting; JAPANESE language; ENGLISH language; MACHINE translating; MODALITY (Linguistics)
- Publication
Language Resources & Evaluation, 2006, Vol 40, Issue 3/4, p233
- ISSN
1574-020X
- Publication type
Article
- DOI
10.1007/s10579-007-9022-z