Word alignment in English-Hindi parallel corpus using recency-vector approach: some studies
Pages 649 - 656
Abstract
Word alignment using recency-vector based approach has recently become popular. One major advantage of these techniques is that unlike other approaches they perform well even if the size of the parallel corpora is small. This makes these algorithms worth-studying for languages where resources are scarce. In this work we studied the performance of two very popular recency-vector based approaches, proposed in (Fung and McKeown, 1994) and (Somers, 1998), respectively, for word alignment in English-Hindi parallel corpus. But performance of the above algorithms was not found to be satisfactory. However, subsequent addition of some new constraints improved the performance of the recency-vector based alignment technique significantly for the said corpus. The present paper discusses the new version of the algorithm and its performance in detail.
References
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K. W. Church Dagan, I. and W. A. Gale. 1993. Robust bilingual word alignment for machine aided translation. In Proc. Workshop on Very Large Corpora: Academic and Industrial Perspectives, pages 1--8, Columbus, Ohio.
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P. Fung and K. McKeown. 1994. Aligning noisy parallel corpora across language groups: Word pair feature matching by dynamic time warping. In Technology Partnerships for Crossing the Language Barrier: Proc. First conference of the Association for Machine Translation in the Americas, pages 81--88, Columbia, Maryland.
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- Word alignment in English-Hindi parallel corpus using recency-vector approach: some studies
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July 2006
1214 pages
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Association for Computational Linguistics
United States
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Published: 17 July 2006
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