융합신호처리학회 학술대회논문집 (Proceedings of the Korea Institute of Convergence Signal Processing)
- 한국신호처리시스템학회 2003년도 하계학술대회 논문집
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- Pages.18-21
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- 2003
GMM을 이용한 프레임 단위 분류에 의한 우리말 음성의 분할과 인식
Korean Speech Segmentation and Recognition by Frame Classification via GMM
초록
In general it has been considered to be the difficult problem that we divide continuous speech into short interval with having identical phoneme quality. In this paper we used Gaussian Mixture Model (GMM) related to probability density to divide speech into phonemes, an initial, medial, and final sound. From them we peformed continuous speech recognition. Decision boundary of phonemes is determined by algorithm with maximum frequency in a short interval. Recognition process is performed by Continuous Hidden Markov Model(CHMM), and we compared it with another phoneme divided by eye-measurement. For the experiments result we confirmed that the method we presented is relatively superior in auto-segmentation in korean speech.
키워드