Part-of-speech tagger for Ainu language based on higher order Hidden Markov Model

要旨

This paper presents POST-AL, the first part-of-speech tagger for Ainu language. The system uses a hand-crafted dictionary based on Ainu narratives “yukar”. The system provides three types of information: word/token, part of speech, and translation of the token (in Japanese). Evaluation on a training set provided positive results. The system could be useful in a great number of tasks related to the research on Ainu language, such as content analysis or translation, which till now have been done mostly manually.

主題