中文摘要：

针对在噪声背景下连续语音信号的语音分割性能会明显下降的问题,提出了一种针对连续语音信号分割的新方法。该方法不再采用单一的端点检测方法,而是将基于分形维数的端点检测方法,基于倒谱特征的端点检测方法,基于HMM的端点检测方法等多种不同方法下得到的端点检测结果,通过投票选择的方式,得到最终的端点检测结果,从而达到对连续语音信号进行分割的目的。实验结果表明,该方法较明显地提高了语音分割的准确性。

英文摘要：

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＇t employ 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 signaLThe experimental results show that the proposed approach rather improves the speech segmentation accuracy.