Alku Paavo, Magi Carlo, Yrttiaho Santeri, Bäckström Tom, Story Brad
Department of Signal Processing and Acoustics, Helsinki University of Technology, P.O. Box 3000, Fi-02015 TKK, Finland.
J Acoust Soc Am. 2009 May;125(5):3289-305. doi: 10.1121/1.3095801.
Closed phase (CP) covariance analysis is a widely used glottal inverse filtering method based on the estimation of the vocal tract during the glottal CP. Since the length of the CP is typically short, the vocal tract computation with linear prediction (LP) is vulnerable to the covariance frame position. The present study proposes modification of the CP algorithm based on two issues. First, and most importantly, the computation of the vocal tract model is changed from the one used in the conventional LP into a form where a constraint is imposed on the dc gain of the inverse filter in the filter optimization. With this constraint, LP analysis is more prone to give vocal tract models that are justified by the source-filter theory; that is, they show complex conjugate roots in the formant regions rather than unrealistic resonances at low frequencies. Second, the new CP method utilizes a minimum phase inverse filter. The method was evaluated using synthetic vowels produced by physical modeling and natural speech. The results show that the algorithm improves the performance of the CP-type inverse filtering and its robustness with respect to the covariance frame position.
闭相（CP）协方差分析是一种广泛使用的声门逆滤波方法，它基于在声门闭相期间对声道的估计。由于闭相的长度通常较短，使用线性预测（LP）进行声道计算容易受到协方差帧位置的影响。本研究基于两个问题提出了对CP算法的改进。首先，也是最重要的，声道模型的计算从传统LP中使用的方法改变为在滤波器优化中对逆滤波器的直流增益施加约束的形式。有了这个约束，LP分析更容易给出符合源-滤波器理论的声道模型；也就是说，它们在共振峰区域显示出复共轭根，而不是在低频处出现不切实际的共振。其次，新的CP方法使用最小相位逆滤波器。该方法使用通过物理建模产生的合成元音和自然语音进行了评估。结果表明，该算法提高了CP型逆滤波的性能及其对协方差帧位置的鲁棒性。
