Modeling long distance dependence in language: topic mixtures versus dynamic cache models

Ostendorf, M; Iyer, R.M.

doi:10.1109/89.736328

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Modeling long distance dependence in language: topic mixtures versus dynamic cache models

Author(s): R.M. Iyer , M. Ostendorf

Publication date (Print): Jan. 1999

Journal: IEEE Transactions on Speech and Audio Processing

Publisher: Institute of Electrical and Electronics Engineers (IEEE)

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Record: found
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An Algorithm for Vector Quantizer Design

Y Linde, A. Buzo, R. Gray (1980)

0 comments Cited 574 times – based on 0 reviews      Review now

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Record: found
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From HMM's to segment models: a unified view of stochastic modeling for speech recognition

O.A. Kimball, V.V. Digalakis, M Ostendorf (1996)

0 comments Cited 56 times – based on 0 reviews      Review now

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A cache-based natural language model for speech recognition

R. Kuhn, R De Mori (1990)

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Author and article information

Journal

Title: IEEE Transactions on Speech and Audio Processing

Abbreviated Title: IEEE Trans. Speech Audio Process.

Publisher: Institute of Electrical and Electronics Engineers (IEEE)

ISSN (Print): 10636676

Publication date (Print): Jan. 1999

Volume: 7

Issue: 1

Pages: 30-39

Article

DOI: 10.1109/89.736328

SO-VID: 5c0ecfbf-6515-4967-b410-fda36387eb58

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