ACLShort '10 Proceedings of the ACL 2010 Conference Short Papers
Hierarchical phrase-based translation grammars extracted from alignment posterior probabilities
EMNLP '10 Proceedings of the 2010 Conference on Empirical Methods in Natural Language Processing
Hierarchical phrase-based translation with weighted finite-state transducers and shallow-n grammars
Computational Linguistics
Explicit length modelling for statistical machine translation
IbPRIA'11 Proceedings of the 5th Iberian conference on Pattern recognition and image analysis
Hierarchical phrase-based translation representations
EMNLP '11 Proceedings of the Conference on Empirical Methods in Natural Language Processing
Explicit length modelling for statistical machine translation
Pattern Recognition
A hidden Markov model for collaborative filtering
MIS Quarterly
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Estimation and alignment procedures for word and phrase alignment hidden Markov models (HMMs) are developed for the alignment of parallel text. The development of these models is motivated by an analysis of the desirable features of IBM Model 4, one of the original and most effective models for word alignment. These models are formulated to capture the desirable aspects of Model 4 in an HMM alignment formalism. Alignment behavior is analyzed and compared to human-generated reference alignments, and the ability of these models to capture different types of alignment phenomena is evaluated. In analyzing alignment performance, Chinese-English word alignments are shown to be comparable to those of IBM Model 4 even when models are trained over large parallel texts. In translation performance, phrase-based statistical machine translation systems based on these HMM alignments can equal and exceed systems based on Model 4 alignments, and this is shown in Arabic-English and Chinese-English translation. These alignment models can also be used to generate posterior statistics over collections of parallel text, and this is used to refine and extend phrase translation tables with a resulting improvement in translation quality.