A Particle Filter algorithm for Bayesian Wordsegmentation

Australasian Language Technology Association Workshop 2011, ALTA 2011 - Proceedings

Volumn , Issue , 2011, Pages 10-18

  Börschinger, Benjamin ^a   Johnson, Mark ^a  

^a MACQUARIE UNIVERSITY   (Australia)

Author keywords

[No Author keywords available]

Indexed keywords

MONTE CARLO METHODS;

A-PARTICLES; BATCH ALGORITHMS; BAYESIAN; BAYESIAN MODELLING; ON-LINE ALGORITHMS; PARTICLE FILTER; PARTICLE FILTER ALGORITHMS; SEGMENTATION MODELS; THEORETICAL GUARANTEES; WORD SEGMENTATION;

BAYESIAN NETWORKS;

EID: 84866859354     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (14)

1. Christopher M. Bishop. 2006. Pattern Recognition and Machine Learning. Springer.
2. Michael R. Brent. 1999. An efficient, probabilistically sound algorithm for segmentation andword discovery. Machine Learning - Special issue on natural language learning, 34:71-105.
3. Kevin Canini, Lei Shi, and Thomas Griffiths. 2009. Online inference of topics with latent dirichlet allocation. In Proceedings of the Twelfth International Conference on Artificial Intelligence and Statistics.
4. Arnaud Doucet, Simon Godsill, and Christophe Andrieu. 2000. On sequential monte carlo sampling methods for bayesian filtering. Statistics and Computing, 10:197-208.
5. Sharon Goldwater, Thomas Griffiths, and Mark Johnson. 2009. A bayesian framework for word segmentation: Exploring the effects of context. Cognition, 112:21-54.
6. Sharon Goldwater. 2007. Nonparametric Bayesian Models of Lexical Acquisition. Ph.D. thesis, Brown University.
7. Mark Johnson and Sharon Goldwater. 2009. Improving nonparameteric bayesian inference: experiments on unsupervised word segmentation with adaptor grammars. In Proceedings of Human Language Technologies: The 2009 Annual Conference of the North American Chapter of the Association for Computational Linguistics, pages 317-325.
8. Mark Johnson, Thomas Griffiths, and Sharon Goldwater. 2007. Bayesian inference for pcfgs via markov chain monte carlo. In Proceedings of NAACL HLT 2007, pages 139-146.
9. Percy Liang and Dan Klein. 2009. Online em for unsupervised models. In Proceedings of NAACL 2009.
10. P. Liang, M. I. Jordan, and D. Klein. 2010. Probabilistic grammars and hierarchical dirichlet processes. In T. O'Hagan and M. West, editors, The Handbook of Applied Bayesian Analysis. Oxford University Press.
11. Bhaskara Marthi, Hanna Pasula, Stuart Russell, and Yuval Peres. 2002. Decayed mcmc filtering. In Proceedings of the Conference on Uncertainty in Artificial Intelligence, 2002 (UAI-02).
12. Daichi Mochihashi, Takeshi Yamada, and Naonori Ueda. 2009. Bayesian unsupervised word segmentation with nested pitman-yor language modeling. In Proceedings of the 47th Annual Meeting of the ACL and the 4th IJCNLP of the AFNLP, page 100108.
13. Lisa Pearl, Sharon Goldwater, and Mark Steyvers. 2011. Online learning mechanisms for bayesian models of word segmentation. Research on Language and Computation, Special issue on computational models of language acquisition.
14. Anand Venkataraman. 2001. A statistical model for word discovery in transcribed speech. Computational Linguistics, 27:351-372.