Automatic Induction of Bilingual Lexicons for Machine Translation

Translation lexicons are one of the most important linguistic resources for machine translation. However, this bilingual set of word and multiword correspondences requires a lot of manual work to be built. This paper describes a method to automatically build translation lexicons. The lexicons are built by extracting knowledge from PoS-tagged and lexically aligned parallel corpora. Preliminary experiments were carried out on Brazilian Portuguese, Spanish and English parallel texts. The results of a manual analysis showed that 85 % of pt-es and 89 % of pt-en entries are plausible correspondences. These results were obtained taking into consideration only the classes of entries which achieved the best results. Target sentences were generated using all induced entries. These sentences were compared with target sentences generated by commercial systems. This comparison emphasizes the relevance of translation lexicons in machine translation, mainly in Portuguese-Spanish