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。
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.
出处
《计算机工程与应用》
CSCD
北大核心
2009年第24期21-24,共4页
Computer Engineering and Applications
基金
国家自然科学基No60702053
黑龙江省自然科学基NoF2004-08~~
