Aggregate and mixed-order Markov models for statistical language processing

Aggregate and mixed-order Markov models for statistical language processing (1997)

Cached

Download Links

Other Repositories/Bibliography

DBLP

by Lawrence Saul , Fernando Pereira

Citations:

80 - 5 self

BibTeX

@MISC{Saul97aggregateand,
    author = {Lawrence Saul and Fernando Pereira},
    title = {Aggregate and mixed-order Markov models for statistical language processing},
    year = {1997}
}

Years of Citing Articles

Bookmark

OpenURL

Abstract

We consider the use of language models whose size and accuracy are intermediate between different order n-gram models.

Citations

8049	Maximum likelihood from incomplete data via the EM algorithm - Dempster, Laird, et al. - 1977
850	An empirical study of smoothing techniques for language modeling - Chen, Goodman - 1998
663	Estimation of probabilities from sparse data for the language model component of a speech recognizer - Katz - 1987
549	Distributional clustering of English words - Pereira, Tishby, et al. - 1993
338	Interpolated estimation of markov source parameters from sparse data,” Pattern Recognit. Practice - Jelinek, Mercer - 1980
242	A maximum entropy approach to adaptive statistical language modeling. Comput Speech Language 10 - Rosenfeld - 1996
169	On structuring probabilistic dependences in stochastic language modeling - Ney, Essen, et al. - 1994
147	The SPHINX-II speech recognition system: an overview”, Computer Speech and Language - Huang, Alleva, et al. - 1993
143	Dimensions of meaning - Schutze - 1992
75	Similarity-based estimation of word co- occurrence probabilities - Dagan, Pereira, et al. - 1994
60	Principles of lexical language modeling for speech recognition - Jelinek, Mercer, et al. - 1991
28	Class-based n-gram models of natural language - Souza, Mercer - 1992
6	Dimensions of meaning - Schfitze - 1992
3	The sphinx speech recognition system: an overview. Computer speech and Language - Huang, al - 1993