| Resumen |
Parallel texts alignment is an active research area in Natural
Language Processing field. In this paper, we propose a method
for sentence alignment of parallel texts that is based both on
lexical and statistical information. The alignment procedure
uses dynamic programming technique. We made our
experiments for Spanish and English texts. We use lexical
information from bilingual Spanish-English dictionary, as well
as the sentence length measured in words and in characters.
The proposed method was tested on a corpus of fiction texts,
where the frequency of multiple alignments, omissions and
insertions is higher than in other types of texts. We obtained
better results than the standard Vanilla aligner system that uses
a purely statistical approach. |
