Conference Paper

Acquisition of Word Translations Using Local Focus-Based Learning in Ainu-Japanese Parallel Corpora.

DOI: 10.1007/978-3-540-24630-5_36 Conference: Computational Linguistics and Intelligent Text Processing, 5th International Conference, CICLing 2004, Seoul, Korea, February 15-21, 2004, Proceedings
Source: DBLP


This paper describes a new learning method for acquisition of word translations from small parallel corpora. Our proposed
method, Local Focus-based Learning (LFL), efficiently acquires word translations and collocation templates by focusing on parts of sentences, not on
entire sentences. Collocation templates have collocation information to acquire word translations from each sentence pair.
This method is useful even when frequency of appearances of word translations is very low in sentence pairs. The LFL system
described in this paper extracts Ainu-Japanese word translations from small Ainu-Japanese parallel corpora. The Ainu language
is spoken by the Ainu ethnic group residing in northern Japan and Sakhalin. An evaluation experiment indicated that the recall
was 57.4% and the precision was 72.0% to 546 kinds of nouns and verbs in 287 Ainu-Japanese sentence pairs even though the
average frequency of appearances of the 546 kinds of nouns and verbs was 1.98.

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