关键词: 语音分割, 倒谱特征, 分形维数, 隐马尔科夫模型（HMM）, 投票选择, 背景噪声

Abstract: Aiming at the question that the performance of speech segmentation declines distinctly in noise environment，this paper proposes a new speech segmentation method for continuous speech signal.The method doesn’temploy a single method for endpoint detection，but combines several different results derived from different endpoint detection methods based on fractal dimension，cepstral feature and HMM model，using a candidate selection approach to get the final boundary in order to segment the continuous speech signal.The experimental results show that the proposed approach rather improves the speech segmentation accuracy.

Key words: speech segmentation, cepstral feature, fractal dimension, Hidden Markov Model（HMM）, candidate selection, noise environment