Continuous speech recognition using hidden Markov models

IEEE ASSP Magazine ◽

10.1109/53.54527 ◽

1990 ◽

Vol 7 (3) ◽

pp. 26-41 ◽

Author(s):

J. Picone

Keyword(s):

Speech Recognition ◽

Hidden Markov Models ◽

Markov Models ◽

Hidden Markov ◽

Continuous Speech ◽

Continuous Speech Recognition

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Speaker Independent Continuous Speech Recognition Using Continuous Density Hidden Markov Models

Speech Recognition and Understanding ◽

10.1007/978-3-642-76626-8_16 ◽

1992 ◽

pp. 135-163 ◽

Author(s):

Chin-Hui Lee ◽

Lawrence R. Rabiner ◽

Roberto Pieraccini

Keyword(s):

Speech Recognition ◽

Hidden Markov Models ◽

Markov Models ◽

Hidden Markov ◽

Continuous Speech ◽

Continuous Speech Recognition ◽

Continuous Density ◽

Speaker Independent

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Large-vocabulary speaker-independent continuous speech recognition with semi-continuous hidden Markov models

Proceedings of the workshop on Speech and Natural Language - HLT '89 ◽

10.3115/1075434.1075480 ◽

1989 ◽

Author(s):

X. D. Huang ◽

H. W. Hon ◽

K. F. Lee

Keyword(s):

Speech Recognition ◽

Hidden Markov Models ◽

Markov Models ◽

Hidden Markov ◽

Continuous Speech ◽

Continuous Speech Recognition ◽

Large Vocabulary ◽

Speaker Independent

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Continuous speech recognition using multilayer perceptrons with hidden Markov models

10.1109/icassp.1990.115720 ◽

2002 ◽

Author(s):

N. Morgan ◽

H. Bourlard

Keyword(s):

Speech Recognition ◽

Hidden Markov Models ◽

Markov Models ◽

Hidden Markov ◽

Multilayer Perceptrons ◽

Continuous Speech ◽

Continuous Speech Recognition

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A comparative study of continuous speech recognition using neural networks and hidden Markov models

[Proceedings] ICASSP 91: 1991 International Conference on Acoustics, Speech, and Signal Processing ◽

10.1109/icassp.1991.150353 ◽

1991 ◽

Author(s):

S. Renals ◽

D. McKelvie ◽

F. McInnes

Keyword(s):

Neural Networks ◽

Speech Recognition ◽

Comparative Study ◽

Hidden Markov Models ◽

Markov Models ◽

Hidden Markov ◽

Continuous Speech ◽

Continuous Speech Recognition

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Environment-independent continuous speech recognition using neural networks and hidden Markov models

1996 IEEE International Conference on Acoustics, Speech, and Signal Processing Conference Proceedings ◽

10.1109/icassp.1996.550597 ◽

2002 ◽

Author(s):

Dong-Suk Yuk ◽

ChiWei Che ◽

Limin Jin ◽

Qiguang Lin

Keyword(s):

Neural Networks ◽

Speech Recognition ◽

Hidden Markov Models ◽

Markov Models ◽

Hidden Markov ◽

Continuous Speech ◽

Continuous Speech Recognition

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Limited‐Vocabulary Estonian Continuous Speech Recognition System using Hidden Markov Models

Informatica ◽

10.15388/informatica.2004.062 ◽

2004 ◽

Vol 15 (3) ◽

pp. 303-314

Author(s):

Tanel Alumäe ◽

Leo Võhandu

Keyword(s):

Speech Recognition ◽

Hidden Markov Models ◽

Markov Models ◽

Hidden Markov ◽

Recognition System ◽

Speech Recognition System ◽

Continuous Speech ◽

Continuous Speech Recognition

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A Configurable Logic Based Architecture for Real-Time Continuous Speech Recognition Using Hidden Markov Models

Field-Programmable Custom Computing Technology: Architectures, Tools, and Applications ◽

10.1007/978-1-4615-4417-3_7 ◽

2000 ◽

pp. 97-114 ◽

Author(s):

Panagiotis Stogiannos ◽

Apostolos Dollas ◽

Vassilis Digalakis

Keyword(s):

Speech Recognition ◽

Hidden Markov Models ◽

Real Time ◽

Markov Models ◽

Hidden Markov ◽

Continuous Speech ◽

Continuous Speech Recognition

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Continuous speech recognition: Hidden markov models vs the connectionist hope

Twenty-Third Asilomar Conference on Signals, Systems and Computers, 1989. ◽

10.1109/acssc.1989.1200807 ◽

1989 ◽

Author(s):

H.A. Bourlard

Keyword(s):

Speech Recognition ◽

Hidden Markov Models ◽

Markov Models ◽

Hidden Markov ◽

Continuous Speech ◽

Continuous Speech Recognition

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An extension of the state-observation dependency in partly hidden Markov models and its application to continuous speech recognition

Systems and Computers in Japan ◽

10.1002/scj.20315 ◽

2005 ◽

Vol 36 (8) ◽

pp. 31-39 ◽

Author(s):

Tetsuji Ogawa ◽

Tetsunori Kobayashi

Keyword(s):

Speech Recognition ◽

Hidden Markov Models ◽

Markov Models ◽

Hidden Markov ◽

The State ◽

Continuous Speech ◽

Continuous Speech Recognition ◽

State Observation

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On the exploitation of hidden Markov models and linear dynamic models in a hybrid decoder architecture for continuous speech recognition

10.21437/interspeech.2010-25 ◽

2010 ◽

Author(s):

Volker Leutnant ◽

Reinhold Haeb-Umbach

Keyword(s):

Speech Recognition ◽

Hidden Markov Models ◽

Dynamic Models ◽

Markov Models ◽

Hidden Markov ◽

Continuous Speech ◽

Continuous Speech Recognition ◽

Linear Dynamic ◽

Decoder Architecture ◽

Linear Dynamic Models

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