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Volume 23 Issue 4
Apr.  2001
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Zhao Li, Zou Cairong, Wu Zhenyang. A METHOD OF HMM SPEECH RECOGNITION INTRODUCED INTER-FRAME CORRELATION[J]. Journal of Electronics & Information Technology, 2001, 23(4): 327-331.
Citation: Zhao Li, Zou Cairong, Wu Zhenyang. A METHOD OF HMM SPEECH RECOGNITION INTRODUCED INTER-FRAME CORRELATION[J]. Journal of Electronics & Information Technology, 2001, 23(4): 327-331.

A METHOD OF HMM SPEECH RECOGNITION INTRODUCED INTER-FRAME CORRELATION

  • Received Date: 1999-06-11
  • Rev Recd Date: 2000-04-23
  • Publish Date: 2001-04-19
  • This paper applies segmental unit into HMM for speech recognition. In this model, several successive frames are combined and treated as an input vector. It expects that segmental unit input HMM would be effective to describe the inter-frame correlation information and has also proposed the MGDF and RBF to further improve output probability function. By comparing them with the traditional HMMs based on their speech recognition performance rates through the experiments of speaker-independent spoken digit (isolated/connected) recognition,the validity of the proposed appraoch could be verified.
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  • V.N. Gupta, M. Lennig, P. Mermelstein, Integration of acoustic information in a large vocabulary word recognizer, ICASSP-87, Dallas, USA, 1987.2, 697-700.[2]坪香英一,ニュ-ラルネツト驱动型HMM, IEICE, Technical Report, 1989, SP89-83, 33-41.[3]L. Deng, M. Aksmanoric, X. Sun, C. F. J. Wu, Speech recognition using hidden Markov models with polynomial regression functions as stationary states, IEEE Trans.[J]. on Speech Audio Processing.1994,(4):507-[4]C.J. Wellekens, Explicit correlation in hidden Maarkov model with optimized inter-frame dependence, ICASSP-95, Detroit, USA, 1995.1,209-212.[5]相川清明,河原英纪,顺向マスキングの时间周波数特性を模拟した动的ケブストラムを用いた音韵识别,日本通信电子学会论文志(A),1993,J76-A(11),1514-1521.[6]井手和之,牧野正三,时间-周波数を用いた无声破裂音の识别,日本音响学会论文志,1982,39(5),321-329.[7]M. Ostendorf, S. Roukos, A stochastic segment model for phoneme-based continuous speech recognition, IEEE Trans. on Acoust..[J]. Speech Signal Processing.1989,ASSP-37(12):1857-[8]T. Wakabayashi, S. Tsuruokaet, ed al., On the size and variable transformation of feature vector for handwritten character, IEICE, J76-D- Ⅱ (12), 2495-2503.[9]L. Zhao, H. Suzuki, S. Nakagawa, A comparison study of probability functions in HMMs through spoken digit recognition, IEICE, TRANS.INF and SYST., 1995, E78-D(6), 669-675.[10]S. Nakagawa, Estimation of probability density function and a posteriori probability and evaluation by vowel recognition, IEICE, Technical Report, 1992, SP92-24, 61-72.
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