A comparison of Bayesian estimators for unsupervised hidden Markov model POS taggers

Jianfeng Gao*, Mark Johnson

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference proceeding contributionpeer-review

66 Citations (Scopus)

Abstract

There is growing interest in applying Bayesian techniques to NLP problems. There are a number of different estimators for Bayesian models, and it is useful to know what kinds of tasks each does well on. This paper compares a variety of different Bayesian estimators for Hidden Markov Model POS taggers with various numbers of hidden states on data sets of different sizes. Recent papers have given contradictory results when comparing Bayesian estimators to Expectation Maximization (EM) for unsupervised HMM POS tagging, and we show that the difference in reported results is largely due to differences in the size of the training data and the number of states in the HMM. We invesigate a variety of samplers for HMMs, including some that these earlier papers did not study. We find that all of Gibbs samplers do well with small data sets and few states, and that Variational Bayes does well on large data sets and is competitive with the Gibbs samplers. In terms of times of convergence, we find that Variational Bayes was the fastest of all the estimators, especially on large data sets, and that explicit Gibbs sampler (both pointwise and sentence-blocked) were generally faster than their collapsed counterparts on large data sets.

Original languageEnglish
Title of host publicationEMNLP 2008
Subtitle of host publication2008 Conference on Empirical Methods in Natural Language Processing: proceedings of the conference
Place of PublicationStroudsburg, PA
PublisherAssociation for Computational Linguistics (ACL)
Pages344-352
Number of pages9
Publication statusPublished - 2008
Externally publishedYes
Event2008 Conference on Empirical Methods in Natural Language Processing, EMNLP 2008, Co-located with AMTA 2008 and the International Workshop on Spoken Language Translation - Honolulu, HI, United States
Duration: 25 Oct 200827 Oct 2008

Other

Other2008 Conference on Empirical Methods in Natural Language Processing, EMNLP 2008, Co-located with AMTA 2008 and the International Workshop on Spoken Language Translation
CountryUnited States
CityHonolulu, HI
Period25/10/0827/10/08

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