Computer Science

Computer Science ›› 2020, Vol. 47 ›› Issue (11A): 172-174.doi: 10.11896/jsjkx.200200006

• Computer Graphics & Multimedia • Previous Articles     Next Articles

Survey of Monosyllable Recognition in Speech Recognition

ZHANG Jing, YANG Jian, SU Peng   

  1. School of Mathematics and Computer Science,Dali University,Dali,Yunnan 671003,China
  • Online:2020-11-15 Published:2020-11-17
  • About author:ZHANG Jing,born in 1997,postgra-duate.Her research interests include speech recognition and deep neural network.
    YANG Jian,born in 1976,Ph.D,asso-ciate professor,is a member of China Computer Federation.His research interests include speech recognition and deep neural network.
  • Supported by:
    This work was supported by the Yunnan Philosophy and Social Sciences Planning Project (YB2017072) and General Project of Joint Fund of Local Colleges and Universities in Yunnan Province(2018FH 001-064).

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Abstract: Acoustic model modeling realizes the processing of speech signals and feature extraction,which is an essential basic work in the process of speech recognition and an important factor affecting the overall performance of speech recognition.In speech recognition,selecting appropriate modeling primitives can make subsequent systems obtain higher accuracy and stronger robustness.Syllable is the smallest pronunciation unit of Sino-Tibetan languages such as Chinese.According to its pronunciation characteristics,it is of great significance to study the use of syllable as the modeling element of Sino-Tibetan language speech re-cognition and to extract the corresponding features for recognition.In view of the current research progress of monosyllabic re-cognition,this paper first introduces the algorithm based on finite state vector quantization and the research results of its improved algorithm in monosyllabic recognition.Then the algorithm based on hidden Markov model is introduced,and the syllable recognition research results combining hidden Markov model with other algorithms are introduced in details,and then the algorithm based on neural network is introduced.Finally,the important development direction of monosyllabic recognition research in the future is summarized and proposed.

Key words: Artificial neural network, Hidden Markov model, Monosyllable recognition, Speech recognition, Vector quantization

CLC Number: 

  • TN912.34
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