(41) Acquisition of Word Translations Using Local Focus-based Learning in
Ainu-Japanese Parallel Corpora
¡¡¡¡¡¡A. Gelbukh (Ed.), Computational Linguistics and
Intelligent Text Processing (CICLing-2004),
¡¡¡¡¡¡Lecture Notes in Computer Science, Springer-Verlag,
VOL.2945, pp.300-304, 2004-2
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.