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Volume 24 Issue 7
Jul.  2002
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Hao Jie, Li Xing . Mandarin continuous speech recognizer based on classical HMM[J]. Journal of Electronics & Information Technology, 2002, 24(7): 944-947.
Citation: Hao Jie, Li Xing . Mandarin continuous speech recognizer based on classical HMM[J]. Journal of Electronics & Information Technology, 2002, 24(7): 944-947.

Mandarin continuous speech recognizer based on classical HMM

  • Received Date: 1900-01-01
  • Rev Recd Date: 1900-01-01
  • Publish Date: 2002-07-19
  • In this paper a mandarin continuous speech recognition system is implemented based on classical Hidden Markov Model (HMM). The performance of classical HMM is quantitatively analyzed and evaluated.
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  • compuer data entry without a keyboard via speech recognition. IEEE Signal Processing Magazine, 1997, 7, 63-101.[5]J.W. Picone, Signal modeling techniques in speech recognition, Proc. of the IEEE, 1993, 81(9),1215-1247.[6]R. Schwartz, S. Austin, A comparison of severel approximate algorithms for finding multiple (N-Best) sentence hypotheses, Proceedings of ICASSP, 1991, Toronto, 701-704. [7]赵庆卫,非特定人大词汇量汉语连续语音识别系统的研究,[博士学位论文],北京,清华大学电子工程系,199.

    863办公室,第五届全国汉字识别、语音识别与合成系统及自然语言处理系统评测结果,智能机研究动态,1998,4.[2]王作英,基于段长分布的HMM语音识别模型,第二届全国汉字语音识别会议,庐山,1989.[3]Wang Zuoying, Gao Hongge, An inhomogeneous HMM speech recognition algorithm.[J]. Proceedings of the first international conference on multimodal interface(ICMI96.1996,Beijing:70-[4]Lee Linshan, Voice dictation of manda.
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