Isolated Mandarin base-syllable recognition based upon the segmentai probability model

Ren Yuan Lyu; I. Chung Hong; Jia Lin Shen; Ming Yu Lee; Lin Shan Lee

doi:10.1109/89.668823

Isolated Mandarin base-syllable recognition based upon the segmentai probability model

Ren Yuan Lyu^*, I. Chung Hong, Jia Lin Shen, Ming Yu Lee, Lin Shan Lee

^*此作品的通信作者

資訊工程學系(含學碩博士班)

研究成果: 期刊稿件 › 文章 › 同行評審

9 引文斯高帕斯（Scopus）

摘要

In this correspondence, a segmental probability model (SPM) is proposed for fast and accurate recognition of the highly confusing isolated Mandarin base-syllables by deleting the state transition probabilities of continuous density hidden Markov models (CHMM), abandoning the dynamic programming process, letting the states equally segment the base-syllables deterministically, and using several special approaches to improve the accuracy and speed. This is achieved by considering the special characteristics of the target vocabulary.

原文	英語
頁（從 - 到）	293-299
頁數	7
期刊	IEEE Transactions on Speech and Audio Processing
卷	6
發行號	3
DOIs	https://doi.org/10.1109/89.668823
出版狀態	已出版 - 1998

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title = "Isolated Mandarin base-syllable recognition based upon the segmentai probability model",

abstract = "In this correspondence, a segmental probability model (SPM) is proposed for fast and accurate recognition of the highly confusing isolated Mandarin base-syllables by deleting the state transition probabilities of continuous density hidden Markov models (CHMM), abandoning the dynamic programming process, letting the states equally segment the base-syllables deterministically, and using several special approaches to improve the accuracy and speed. This is achieved by considering the special characteristics of the target vocabulary.",

keywords = "Hidden markov model, Isolated syllable, Mandarin chinese, Segmental probability model, Speech recognition",

author = "Lyu, \{Ren Yuan\} and Hong, \{I. Chung\} and Shen, \{Jia Lin\} and Lee, \{Ming Yu\} and Lee, \{Lin Shan\}",

year = "1998",

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language = "英语",

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AU - Lyu, Ren Yuan

AU - Hong, I. Chung

AU - Shen, Jia Lin

AU - Lee, Ming Yu

AU - Lee, Lin Shan

PY - 1998

Y1 - 1998

N2 - In this correspondence, a segmental probability model (SPM) is proposed for fast and accurate recognition of the highly confusing isolated Mandarin base-syllables by deleting the state transition probabilities of continuous density hidden Markov models (CHMM), abandoning the dynamic programming process, letting the states equally segment the base-syllables deterministically, and using several special approaches to improve the accuracy and speed. This is achieved by considering the special characteristics of the target vocabulary.

AB - In this correspondence, a segmental probability model (SPM) is proposed for fast and accurate recognition of the highly confusing isolated Mandarin base-syllables by deleting the state transition probabilities of continuous density hidden Markov models (CHMM), abandoning the dynamic programming process, letting the states equally segment the base-syllables deterministically, and using several special approaches to improve the accuracy and speed. This is achieved by considering the special characteristics of the target vocabulary.

KW - Hidden markov model

KW - Isolated syllable

KW - Mandarin chinese

KW - Segmental probability model

KW - Speech recognition

UR - https://www.scopus.com/pages/publications/0032070029

U2 - 10.1109/89.668823

DO - 10.1109/89.668823

M3 - 文章

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EP - 299

JO - IEEE Transactions on Speech and Audio Processing

JF - IEEE Transactions on Speech and Audio Processing

IS - 3

ER -

Isolated Mandarin base-syllable recognition based upon the segmentai probability model

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