Bayesian word alignment for statistical machine translation

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This is our reading group slides. For ACL 2011 Poster paper: Bayesian Word Alignment for Statistical Machine Translation

Bayesian Word Alignment for Statistical Machine Translation Authors: Coskun Mermer, Murat Saraclar Present by Jun Lang 2011-10-13 I2R SMT-Reading Group

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Dirichlet Distribution Each source word type te is a distribution over the target vocabulary, to be a Dirichlet distribution Avoid rare words acting as “garbage collectors”

Dirichlet Distribution sample the unknowns A and T in turn ¬j denotes the exclusion of the current value of aj .

Algorithm A can be arbitrary, but normal EM output is better

Conclusions ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]

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Bayesian word alignment for statistical machine translation

1. Bayesian Word Alignment for Statistical Machine Translation Authors: Coskun Mermer, Murat Saraclar Present by Jun Lang 2011-10-13 I2R SMT-Reading Group

5. IBM Model 1 T as a random variable

7. Dirichlet Distribution Each source word type te is a distribution over the target vocabulary, to be a Dirichlet distribution Avoid rare words acting as “garbage collectors”

8. Dirichlet Distribution sample the unknowns A and T in turn ¬j denotes the exclusion of the current value of aj .

9. Algorithm A can be arbitrary, but normal EM output is better

10. Results

11.

12.

13. Code View bayesalign.pl

14.

15. 3