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COLING
1996

Aligning More Words with High Precision for Small Bilingual Corpora

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Aligning More Words with High Precision for Small Bilingual Corpora
In this paper, we propose an algorithm for identifying each word with its translations in a sentence and translation pair. Previously proposed methods require enormous amounts of bilingual data to train statistical word-by-word translation models. By taking a word-based approach, these methods align frequent words with consistent translations at a high precision rate. However, less frequent words or words with diverse translations generally do not have statistically significant evidence for confident alignment. Consequently, incomplete or incorrect alignments occur. Here, we attempt to improve on the coverage using class-based rules. An automatic procedure for acquiring such rules is also described. Experimental results confirm that the algorithm can align over 85% of word pairs while maintaining a comparably high precision rate, even when a small corpus is used in training.
Sur-Jin Ker, Jason J. S. Chang
Added 02 Nov 2010
Updated 02 Nov 2010
Type Conference
Year 1996
Where COLING
Authors Sur-Jin Ker, Jason J. S. Chang
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