Discrete utterance recognition based on nonlinear model identification with single layer neural networks

Sam KWONG; Gang WEI; Yiu-Keung CHAN; Jing-Zheng OUYANG

doi:10.1109/ISCAS.1993.394252

Discrete utterance recognition based on nonlinear model identification with single layer neural networks

Sam KWONG, Gang WEI, Yiu-Keung CHAN, Jing-Zheng OUYANG

Research output: Book Chapters | Papers in Conference Proceedings › Conference paper (refereed) › Research › peer-review

Abstract

In this paper, a scheme for speaker independent discrete utterance recognition using single layer neural network (SLNN) based nonlinear auto regression model parameters as the features is presented. A fast training algorithm is developed for the identification of the model parameters. Dynamic programming is used for the pattern matching. The experimental results of speaker independent recognition of 10 digits are reported.

Original language	English
Title of host publication	Proceedings - IEEE International Symposium on Circuits and Systems
Publisher	IEEE
Pages	2419-2422
ISBN (Print)	0780312813
DOIs	https://doi.org/10.1109/ISCAS.1993.394252
Publication status	Published - May 1993
Externally published	Yes
Event	1993 IEEE International Symposium on Circuits and Systems (ISCAS) - Chicago, United States Duration: 3 May 2023 → 6 May 2023

Conference

Conference	1993 IEEE International Symposium on Circuits and Systems (ISCAS)
Country/Territory	United States
City	Chicago
Period	3/05/23 → 6/05/23

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10.1109/ISCAS.1993.394252

Cite this

@inproceedings{16e216bfb1ef42e091542ade69ce6c2b,

title = "Discrete utterance recognition based on nonlinear model identification with single layer neural networks",

abstract = "In this paper, a scheme for speaker independent discrete utterance recognition using single layer neural network (SLNN) based nonlinear auto regression model parameters as the features is presented. A fast training algorithm is developed for the identification of the model parameters. Dynamic programming is used for the pattern matching. The experimental results of speaker independent recognition of 10 digits are reported.",

author = "Sam KWONG and Gang WEI and Yiu-Keung CHAN and Jing-Zheng OUYANG",

year = "1993",

month = may,

doi = "10.1109/ISCAS.1993.394252",

language = "English",

isbn = "0780312813",

pages = "2419--2422",

booktitle = "Proceedings - IEEE International Symposium on Circuits and Systems",

publisher = "IEEE",

note = "1993 IEEE International Symposium on Circuits and Systems (ISCAS) ; Conference date: 03-05-2023 Through 06-05-2023",

}

KWONG, S, WEI, G, CHAN, Y-K & OUYANG, J-Z 1993, Discrete utterance recognition based on nonlinear model identification with single layer neural networks. in Proceedings - IEEE International Symposium on Circuits and Systems. IEEE, pp. 2419-2422, 1993 IEEE International Symposium on Circuits and Systems (ISCAS), Chicago, United States, 3/05/23. https://doi.org/10.1109/ISCAS.1993.394252

Discrete utterance recognition based on nonlinear model identification with single layer neural networks. / KWONG, Sam; WEI, Gang; CHAN, Yiu-Keung et al.
Proceedings - IEEE International Symposium on Circuits and Systems. IEEE, 1993. p. 2419-2422.

Research output: Book Chapters | Papers in Conference Proceedings › Conference paper (refereed) › Research › peer-review

TY - GEN

T1 - Discrete utterance recognition based on nonlinear model identification with single layer neural networks

AU - KWONG, Sam

AU - WEI, Gang

AU - CHAN, Yiu-Keung

AU - OUYANG, Jing-Zheng

PY - 1993/5

Y1 - 1993/5

N2 - In this paper, a scheme for speaker independent discrete utterance recognition using single layer neural network (SLNN) based nonlinear auto regression model parameters as the features is presented. A fast training algorithm is developed for the identification of the model parameters. Dynamic programming is used for the pattern matching. The experimental results of speaker independent recognition of 10 digits are reported.

AB - In this paper, a scheme for speaker independent discrete utterance recognition using single layer neural network (SLNN) based nonlinear auto regression model parameters as the features is presented. A fast training algorithm is developed for the identification of the model parameters. Dynamic programming is used for the pattern matching. The experimental results of speaker independent recognition of 10 digits are reported.

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U2 - 10.1109/ISCAS.1993.394252

DO - 10.1109/ISCAS.1993.394252

M3 - Conference paper (refereed)

SN - 0780312813

SP - 2419

EP - 2422

BT - Proceedings - IEEE International Symposium on Circuits and Systems

PB - IEEE

T2 - 1993 IEEE International Symposium on Circuits and Systems (ISCAS)

Y2 - 3 May 2023 through 6 May 2023

ER -

Discrete utterance recognition based on nonlinear model identification with single layer neural networks

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