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      상태수 변화에 따른 NNPHMM의 성능비교 = A COMPARATIVE STUDY OF NNPHMM ACCORDING TO THE VARIATION OF STATE NUMBER

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      https://www.riss.kr/link?id=A2006681

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      In this paper, we compose neural predictive HMM(NNPHMM) to provide the dynamic feature of the speech pattern for the HMM. The NNPHMM is the hybrid network of neural network and the HMM. The NNPHMM trained to predict the future vector, varies each time. It is used instead of the mean vector in the HMM. In the experiment, we compared the recognition abilities of the one hundred Korean syllables according to the variation of state number and prediction order. The state number of the NNPHMM increased from 4 to 6. And the prediction orders increased from 2nd to 4th order. The NNPHMM in the experiment is composed of multi-layer perceptron with one hidden layer and CMHMM. As a result of the experiment, the average recognition rates are 85.2%, 85.6% and 85.5% when the state number is 5, the prediction order is the 2nd, 3rd, 4th, and the hidden layer is 10 dimensions, respectively.

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      In this paper, we compose neural predictive HMM(NNPHMM) to provide the dynamic feature of the speech pattern for the HMM. The NNPHMM is the hybrid network of neural network and the HMM. The NNPHMM trained to predict the future vector, varies each time...

      In this paper, we compose neural predictive HMM(NNPHMM) to provide the dynamic feature of the speech pattern for the HMM. The NNPHMM is the hybrid network of neural network and the HMM. The NNPHMM trained to predict the future vector, varies each time. It is used instead of the mean vector in the HMM. In the experiment, we compared the recognition abilities of the one hundred Korean syllables according to the variation of state number and prediction order. The state number of the NNPHMM increased from 4 to 6. And the prediction orders increased from 2nd to 4th order. The NNPHMM in the experiment is composed of multi-layer perceptron with one hidden layer and CMHMM. As a result of the experiment, the average recognition rates are 85.2%, 85.6% and 85.5% when the state number is 5, the prediction order is the 2nd, 3rd, 4th, and the hidden layer is 10 dimensions, respectively.

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