一种基于加权Mel倒谱的语音信号共振峰提取算法

A formant extraction algorithm of speech signal based on weighted Mel-cepstrum

提出了一种利用加权Mel倒谱提取语音信号共振峰的算法.首先对短时语音信号进行加权Mel倒谱分析,获得包含频谱主要成分的加权Mel倒谱系数;然后利用离散余弦平滑算法,从加权Mel倒谱系数获得谱包络,并从谱包络的峰值位置获得候选共振峰;最后根据共振峰的连续性约束条件和频率范围,从候选共振峰筛选得到共振峰的估计值.实验结果表明,本算法比倒谱法提取的共振峰误差更小,在噪声环境下具有较好的鲁棒性.

This paper presents a method to realize formants extraction from speech signal.The weighted Mel-cepstrum coefficients（WMCC）,which contain main components of spectrum,are obtained from speech signal by using weighted Mel-cepstrum analysis.The discrete cosine transform （DCT） based smooth algorithm is then applied to the WMCCs to obtain the smooth contour of spectrum in which the peaks of contour are candidate formants.The formant frequencies are selected from candidate formants according to the continuity constrain and the frequency range of formants.Tests show that the errors of this method outperform the cepstrum based method.The method is also robust on noisy speech signal.