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안태옥,이강성,유형근,이형준,조형제,변용규,김순협,Ann, T.O.,Lee, K.S.,Yoo, H.K.,Lee, H.J.,Cho, H.J.,Byun, Y.G.,Kim, S.H. 한국음향학회 1991 韓國音響學會誌 Vol.10 No.1
This paper describes the study on isolated word recognition by using DHMM(Dynamic Hidden Markov Model) which has dynamic feature of spectrum as a parameter. This paper discusses speech recognition experiment basedon HMM which can evaluate not only instantaneous spectral features but also dynamic spectral features. LPC cepstrum parameters is used as a static feature and LPC cepstrum's regression coefficient is used as a dynamic feature. These two features are quantized by each VQ codebook. DHMM is modeled by receiving static vector and dynamic vector by input. In the whole experiment, as recognition experiment using DHMM shows 92.7% of recognition rate while the experiment using conventional HMM shows 88.8% of recognition rate, DHMM proved to be a useful model.