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Improving IBM Word Alignment Model 1

. Proceedings of the 42nd Annual Meeting of the Association for Computational Linguistics, Barcelona, Spain, page 518-525. (2004)

Abstract

We investigate a number of simple methods for improving the word-alignment accuracy of IBM Model 1. We demonstrate reduction in alignment error rate of approximately 30% resulting from (1) giving extra weight to the probability of alignment to the null word, (2) smoothing probability estimates for rare words, and (3) using a simple heuristic estimation method to initialize, or replace, EM training of model parameters.

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