Identifying word correspondence in parallel texts
HLT '91 Proceedings of the workshop on Speech and Natural Language
Translating collocations for bilingual lexicons: a statistical approach
Computational Linguistics
Bilingual Sentence Alignment: Balancing Robustness and Accuracy
Machine Translation
Bitext maps and alignment via pattern recognition
Computational Linguistics
A word-to-word model of translational equivalence
ACL '98 Proceedings of the 35th Annual Meeting of the Association for Computational Linguistics and Eighth Conference of the European Chapter of the Association for Computational Linguistics
A simple hybrid aligner for generating lexical correspondences in parallel texts
COLING '98 Proceedings of the 17th international conference on Computational linguistics - Volume 1
Aligning sentences in parallel corpora
ACL '91 Proceedings of the 29th annual meeting on Association for Computational Linguistics
Char_align: a program for aligning parallel texts at the character level
ACL '93 Proceedings of the 31st annual meeting on Association for Computational Linguistics
Using confidence bands for parallel texts alignment
ACL '00 Proceedings of the 38th Annual Meeting on Association for Computational Linguistics
The english unknown term translation mining with improved bilingual snippets collection strategy
ICIC'12 Proceedings of the 8th international conference on Intelligent Computing Theories and Applications
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Most methods to extract bilingual lexicons from parallel corpora learn word correspondences using relative small aligned segments, called sentences. Then, they need to get a corpus aligned at the sentence level. Such an alignment can require further manual corrections if the parallel corpus contains insertions, deletions, or fuzzy sentence boundaries. This paper shows that it is possible to extract bilingual lexicons without aligning parallel texts at the sentence level. We describe a method to learn word translations from a very roughly aligned corpus, namely a corpus with quite long segments separated by “natural boundaries”. The results obtained using this method are very close to those obtained using sentence alignment. Some experiments were performed on English-Portuguese and English-Spanish parallel texts.