Proceedings of the IEEK Conference (대한전자공학회:학술대회논문집)
- 2003.07e
- /
- Pages.2220-2223
- /
- 2003
Research about auto-segmentation via SVM
SVM을 이용한 자동 음소분할에 관한 연구
Abstract
In this paper we used Support Vector Machines(SVMs) recently proposed as the loaming method, one of Artificial Neural Network, to divide continuous speech into phonemes, an initial, medial, and final sound, and then, performed continuous speech recognition from it. Decision boundary of phoneme 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. From experiment we confirmed that the method, SVMs, we proposed is more effective in an initial sound than Gaussian Mixture Models(GMMs).
Keywords