Extensions to HMM-based Statistical Word Alignment Models

Extensions to HMM-based Statistical Word Alignment Models (2002)

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by Kristina Toutanova , H. Tolga Ilhan , Christopher D. Manning

Venue:	In Proc. of EMNLP
Citations:	15 - 0 self

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@INPROCEEDINGS{Toutanova02extensionsto,
    author = {Kristina Toutanova and H. Tolga Ilhan and Christopher D. Manning},
    title = {Extensions to HMM-based Statistical Word Alignment Models},
    booktitle = {In Proc. of EMNLP},
    year = {2002},
    pages = {87--94}
}

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Abstract

This paper describes improved HMM-based word level alignment models for statistical machine translation. We present a method for using part of speech tag information to improve alignment accuracy, and an approach to modeling fertility and correspondence to the empty word in an HMM alignment model. We present accuracy results from evaluating Viterbi alignments against human-judged alignments on the Canadian Hansards corpus, as compared to a bigram HMM, and IBM model 4.

Citations

341	Improved statistical alignment models - Och, Ney - 2000
205	Improved alignment models for statistical machine translation - Och, Tillmann, et al. - 1999
155	HMM-based word alignment in statistical translation - Vogel, Ney, et al. - 1996
121	Models of translational equivalence among words - Melamed
2	Coerced markov models for cross-lingual tag relations - Fung, Wu - 1995