A hierarchical dirichlet process model for joint part-of-speech and morphology induction

NAACL HLT 2012 - 2012 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Proceedings of the Conference

Volumn , Issue , 2012, Pages 407-416

  Sirts, Kairit ^a   Alumäe, Tanel ^a  

^a TALLINN UNIVERSITY OF TECHNOLOGY   (Estonia)

Author keywords

[No Author keywords available]

Indexed keywords

BAYESIAN NETWORKS;

GOLD STANDARDS; HIERARCHICAL DIRICHLET PROCESS; JOINT PARTS; MORPHOLOGICAL FEATURES; MORPHOLOGICAL SEGMENTATION; NON-PARAMETRIC BAYESIAN MODELING; NUMBER OF STATE; PART OF SPEECH; PRE-PROCESSING STEP; PROCESS-MODELS;

MORPHOLOGY;

EID: 84880327276     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (25)

1. D. Aldous. 1985. Exchangeability and related topics. In Ećole d'été de Probabilités de Saint-Flour, XIII- 1983, pages 1-198. Springer.
2. Taylor Berg-Kirkpatrick, Alexandre Bouchard-Côté, John DeNero, and Dan Klein. 2010. Painless unsupervised learning with features. In Human Language Technologies: The 2010 Annual Conference of the North American Chapter of the Association for Computational Linguistics, pages 582-590.
3. Phil Blunsom and Trevor Cohn. 2011. A hierarchical Pitman-Yor process HMM for unsupervised Part of Speech induction. In Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies - Volume 1, pages 865-874.
4. Christos Christodoulopoulos, Sharon Goldwater, and Mark Steedman. 2010. Two decades of unsupervised POS induction: How far have we come? In Proceedings of the 2010 Conference on Empirical Methods in Natural Language Processing, pages 575-584.
5. Christos Christodoulopoulos, Sharo Goldwater, and Mark Steedman. 2011. A Bayesian mixture model for PoS induction using multiple features. In Proceedings of the 2011 Conference on Empirical Methods in Natural Language Processing, pages 638-647, Edinburgh, Scotland, UK.
6. Alexander Clark. 2003. Combining distributional and morphological information for Part of Speech induction. In Proceedings of the Tenth Conference on European Chapter of the Association for Computational Linguistics - Volume 1, pages 59-66.
7. Mathias Creutz and Krista Lagus. 2005. Inducing the morphological lexicon of a natural language from unannotated text. In In Proceedings of the International and Interdisciplinary Conference on Adaptive Knowledge Representation and Reasoning, pages 106-113.
8. Markus Dreyer and Jason Eisner. 2011. Discovering morphological paradigms from plain text using a Dirichlet Process mixture model. In Proceedings of the 2011 Conference on Empirical Methods in Natural Language Processing, pages 616-627.
9. Toma Erjavec. 2010. MULTEXT-East version 4: Multilingual morphosyntactic specifications, lexicons and corpora. In Proceedings of the Seventh International Conference on Language Resources and Evaluation.
10. Michael D. Escobar and Mike West. 1995. Bayesian density estimation and inference using mixtures. Journal of the American Statistical Association, 90(430).
11. Thomas S. Ferguson. 1973. A Bayesian analysis of some nonparametric problems. The Annals of Statistics, 1(2):209-230.
12. Jurgen Van Gael, Yunus Saatci, Yee Whye Teh, and Zoubin Ghahramani. 2008. Beam sampling for the infinite Hidden Markov Model. In Proceedings of the 25th International Conference on Machine Learning, pages 1088-1095.
13. Jurgen Van Gael, Andreas Vlachos, and Zoubin Ghahramani. 2009. The infinite HMM for unsupervised PoS tagging. In Proceedings of the 2009 Conference on Empirical Methods in Natural Language Processing: Volume 2 - Volume 2, pages 678-687.
14. Sharon Goldwater and Tom Griffiths. 2007. A fully Bayesian approach to unsupervised Part-of-Speech tagging. In Proceedings of the 45th Annual Meeting of the Association of Computational Linguistics, pages 744-751, Prague, Czech Republic.
15. Sharon Goldwater, Thomas L. Griffiths, and Mark Johnson. 2006. Interpolating between types and tokens by estimating power-law generators. In Advances in Neural Information Processing Systems 18, Cambridge, MA.
16. Sharon Goldwater, Thomas L. Griffiths, and Mark Johnson. 2009. A Bayesian framework for word segmentation: Exploring the effects of context. Cognition, 112:21-54.
17. Aria Haghighi and Dan Klein. 2006. Prototype-driven learning for sequence models. In Proceedings of the Human Language Technology Conference of the NAACL, Main Conference, pages 320-327, New York City, USA.
18. Mark Johnson, Thomas L. Griffiths, and Sharon Goldwater. 2006. Adaptor grammars: A framework for specifying compositional nonparametric Bayesian models. In Advances in Neural Information Processing Systems 19, pages 641-648.
19. Yoong Keok Lee, Aria Haghighi, and Regina Barzilay. 2010. Simple type-level unsupervised POS tagging. In Proceedings of the 2010 Conference on Empirical Methods in Natural Language Processing, pages 853-861.
20. Daichi Mochihashi, Takeshi Yamada, and Naonori Ueda. 2009. Bayesian unsupervised word segmentation with nested Pitman-Yor language modeling. In Proceedings of the Joint Conference of the 47th Annual Meeting of the ACL and the 4th International Joint Conference on Natural Language Processing of the AFNLP: Volume 1 - Volume 1, pages 100-108.
21. Tahira Naseem, Benjamin Snyder, Jacob Eisenstein, and Regina Barzilay. 2009. Multilingual part-of-speech tagging: Two unsupervised approaches. Journal of Artificial Intelligence Research, 36:1-45.
22. Lawrence R. Rabiner. 1989. A tutorial on Hidden Markov Models and selected applications in speech recognition. In Proceedings of the IEEE, pages 257-286.
23. Andrew Rosenberg and Julia Hirschberg. 2007. Vmeasure: A conditional entropy-based external cluster evaluation measure. In Proceedings of the 2007 Joint Conference on Empirical Methods in Natural Language Processing and Computational Natural Language Learning (EMNLP-CoNLL), pages 410-420, Prague, Czech Republic.
24. Yee Whye Teh, Michel I. Jordan, Matthew J. Beal, and David M. Blei. 2006. Hierarchical Dirichlet processes. Journal of the American Statistical Association, 101(476):1566-1581.
25. Yee Whye Teh. 2006. A hierarchical Bayesian language model based on Pitman-Yor processes. In Proceedings of the 21st International Conference on Computational Linguistics and 44th Annual Meeting of the Association for Computational Linguistics, pages 985-992.