DeNero et al, EMNLP 2008
Contents
Citation
Denero, J., Bouchard-ct, R., & Klein, D.(2008). Sampling alignment structure under a Bayesian translation model. In Proceedings of the Conference on Empirical Methods in Natural Language Processing (EMNLP '08). Association for Computational Linguistics, Stroudsburg, PA, USA, 314-323.
Online version
Summary
Unlike word-to-phrase alignments, computing the alignment expectations for phrase-to-phrase alignments is generally intractable due to the exponential growth of possible combination of phrases and alignments. Because of this, previous attempts for building a joint phrase alignment model have been unsuccessful.
This paper describes the first tractable phrase-to-phrase Alignment Model, which relies on Gibbs Sampling to tackle the intractability problem.
Tests show translation improvements over Machine Translation Systems build using conventional methods.
