A program for aligning sentences in bilingual corpora
Computational Linguistics - Special issue on using large corpora: I
Computational Linguistics - Special issue on using large corpora: I
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
A program for aligning sentences in bilingual 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
Aligning sentences in bilingual corpora using lexical information
ACL '93 Proceedings of the 31st annual meeting on Association for Computational Linguistics
Aligning a parallel English-Chinese corpus statistically with lexical criteria
ACL '94 Proceedings of the 32nd annual meeting on Association for Computational Linguistics
Bilingual text, matching using bilingual dictionary and statistics
COLING '94 Proceedings of the 15th conference on Computational linguistics - Volume 2
Has There Been a Revolution in Machine Translation?
Machine Translation
A Multilingual Procedure for Dictionary-Based Sentence Alignment
AMTA '98 Proceedings of the Third Conference of the Association for Machine Translation in the Americas on Machine Translation and the Information Soup
Automatic extraction of bilingual word pairs using inductive chain learning in various languages
Information Processing and Management: an International Journal
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The task of aligning sentences in parallel corpora of two languages has been well studied using pure statistical or linguistic models. We developed a linguistic method based on lexical matching with a bilingual dictionary and two statistical methods based on sentence length ratios and sentence offset probabilities. This paper seeks to further our knowledge of the alignment task by comparing the performance of the alignment models when used separately and together, i.e. as a hybrid system. Our results show that for our English-Japanese corpus of newspaper articles, the hybrid system using lexical matching and sentence length ratios outperforms the pure methods.