Maximum entropy techniques for exploiting syntactic, semantic and collocational dependencies in language modeling

Sanjeev Khudanpur; Jun Wu

doi:10.1006/csla.2000.0149

Maximum entropy techniques for exploiting syntactic, semantic and collocational dependencies in language modeling

Computer Speech & Language ◽

10.1006/csla.2000.0149 ◽

2000 ◽

Vol 14 (4) ◽

pp. 355-372 ◽

Cited By ~ 38

Author(s):

Sanjeev Khudanpur ◽

Jun Wu

Keyword(s):

Maximum Entropy ◽

Language Modeling

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Sparse Non-Negative Matrix Language Modeling: Maximum Entropy Flexibility on the Cheap

10.21437/interspeech.2017-493 ◽

2017 ◽

Cited By ~ 1

Author(s):

Ciprian Chelba ◽

Diamantino Caseiro ◽

Fadi Biadsy

Keyword(s):

Maximum Entropy ◽

Language Modeling

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Smoothing methods in maximum entropy language modeling

1999 IEEE International Conference on Acoustics, Speech, and Signal Processing. Proceedings. ICASSP99 (Cat. No.99CH36258) ◽

10.1109/icassp.1999.758183 ◽

1999 ◽

Cited By ~ 7

Author(s):

S.C. Martin ◽

H. Ney ◽

J. Zaplo

Keyword(s):

Maximum Entropy ◽

Language Modeling ◽

Smoothing Methods

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Semantic n-gram language modeling with the latent maximum entropy principle

2003 IEEE International Conference on Acoustics, Speech, and Signal Processing, 2003. Proceedings. (ICASSP '03). ◽

10.1109/icassp.2003.1198796 ◽

2003 ◽

Cited By ~ 1

Author(s):

Shaojun Wang ◽

D. Schuurmans ◽

Fuchun Peng ◽

Yunxin Zhao

Keyword(s):

Maximum Entropy ◽

Maximum Entropy Principle ◽

Language Modeling ◽

Entropy Principle ◽

N Gram

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Latent maximum entropy principle for statistical language modeling

IEEE Workshop on Automatic Speech Recognition and Understanding, 2001. ASRU '01. ◽

10.1109/asru.2001.1034617 ◽

2005 ◽

Author(s):

Shaojun Wang ◽

R. Rosenfeld ◽

Yunxin Zhao

Keyword(s):

Maximum Entropy ◽

Maximum Entropy Principle ◽

Language Modeling ◽

Statistical Language Modeling ◽

Entropy Principle

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Maximum entropy language modeling and the smoothing problem

IEEE Transactions on Speech and Audio Processing ◽

10.1109/89.861385 ◽

2000 ◽

Vol 8 (5) ◽

pp. 626-632 ◽

Cited By ~ 4

Author(s):

S.C. Martin ◽

H. Ney ◽

C. Hamacher

Keyword(s):

Maximum Entropy ◽

Language Modeling

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Adaptive language modeling using the maximum entropy principle

Proceedings of the workshop on Human Language Technology - HLT '93 ◽

10.3115/1075671.1075695 ◽

1993 ◽

Cited By ~ 13

Author(s):

Raymond Lau ◽

Ronald Rosenfeld ◽

Salim Roukos

Keyword(s):

Maximum Entropy ◽

Maximum Entropy Principle ◽

Language Modeling ◽

Entropy Principle

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Investigation of Sampling Techniques for Maximum Entropy Language Modeling Training

ICASSP 2019 - 2019 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) ◽

10.1109/icassp.2019.8683017 ◽

2019 ◽

Cited By ~ 1

Author(s):

Xie Chen ◽

Jun Zhang ◽

Tasos Anastasakos ◽

Fil Alleva

Keyword(s):

Maximum Entropy ◽

Language Modeling ◽

Sampling Techniques

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Stochasting modeling of planetary ring systems

International Astronomical Union Colloquium ◽

10.1017/s025292110010154x ◽

1984 ◽

Vol 75 ◽

pp. 461-469 ◽

Cited By ~ 1

Author(s):

Robert W. Hart

Keyword(s):

Maximum Entropy ◽

Ring System ◽

The Sun ◽

Ultimate State ◽

Interparticle Interactions ◽

Ring Systems ◽

First Order ◽

Planetary Ring ◽

Insight Into

ABSTRACTThis paper models maximum entropy configurations of idealized gravitational ring systems. Such configurations are of interest because systems generally evolve toward an ultimate state of maximum randomness. For simplicity, attention is confined to ultimate states for which interparticle interactions are no longer of first order importance. The planets, in their orbits about the sun, are one example of such a ring system. The extent to which the present approximation yields insight into ring systems such as Saturn's is explored briefly.

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