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Improving IBM Word-Alignment Model 1

By Robert C. Moore

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

Year: 2009
OAI identifier: oai:CiteSeerX.psu:10.1.1.134.4772
Provided by: CiteSeerX
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