Statistical models of syntax learning and use

Cognitive Science

Volumn 26, Issue 3, 2002, Pages 239-253

  Johnson, Mark ^a   Riezler, Stefan ^b  

^a BROWN UNIVERSITY   (United States)

^b PALO ALTO RESEARCH CENTER   (United States)

Author keywords

Discriminative parameter estimation; Maximum entropy modeling; Statistical language learning; Statistical parsing

Indexed keywords

EID: 0036083973     PISSN: 03640213     EISSN: None     Source Type: Journal    
DOI: 10.1016/S0364-0213(02)00068-X     Document Type: Article

References (23)

1. Stochastic attribute-value grammars
2. Relating probabilistic grammars and automata
3. A maximum entropy approach to natural language processing
4. Statistical analysis of non-lattice data
5. The mental representation of grammatical relations
6. Cross-serial dependencies in Dutch
7. Probability models for complex systems
8. Statistical properties of probabilistic context-free grammars
9. Maximum likelihood from incomplete data via the EM algorithm
10. Graphical models for machine learning and digital communication
11. Language identification in the limit
12. Two principles of parse preference
13. A study of grammatical inference
14. Statistical methods for speech recognition
15. Estimators for stochastic "unification-based" grammars
16. Exploiting auxiliary distributions in stochastic unification-based grammars
17. The formal architecture of LFG
18. Long-distance dependencies, constituent structure and functional uncertainty
19. The interface between phrasal and functional constraints
20. Lexicalized stochastic modeling of constraint-based grammars using log-linear measures and EM training
21. A mean field learning algorithm for unsupervised neural networks
22. Evidence against the context-freeness of natural language
23. Error bounds for convolutional codes and an asymptotically optimum decoding algorithm