基于匹配跟踪的感知梯度正弦建模方法

A Sinusoidal Modeling Method Based on Matching-Pursuits with Perceptual Gradient

匹配跟踪作为一种自适应的信号分解算法,为语音和音频正弦建模提供了一个新的框架.分析了基于匹配跟踪的正弦建模过程以及感知加权匹配跟踪正弦建模算法,并在此基础上提出了感知梯度正弦建模方法.该方法结合匹配跟踪自适应的动态特征,利用心理声学模型计算当前合成信号的动态掩蔽阈值,以此为参考提取残差信号中感觉最明显的信号分量,从而最大限度地增加合成信号中的感知信息.在模型精度不高的情况下,该方法也能得到合成质量比较高的语音.实验表明,该方法更好地利用了人耳的听觉特性,建模结果更为合理、有效.客观的信噪比和主观试听测试都显示了所提出算法的合理性与优越性.

As an adaptive algorithm of signal decomposition, matching pursuits provides a new framework for sinusoidal modeling of speech and audio signal. In this paper, the procedure of sinusoidal modeling using matching pursuits is analyzed as well as the sinusoidal modeling algorithm using perceptually weighted matching pursuits. And a method of sinusoidal modeling with perceptual gradient is proposed. The proposed method, which adopts the adaptive feature of matching pursuits, computes dynamically a masking threshold from the currently synthesized signal using the psychoacoustic model. With the threshold, it extracts the most perceptually significant component from the residual signal. Therefore, the perceptual information contained in the synthesized signal increases as quickly as possible. The quality of the synthesized speech by this approach is rather high even if the model precision is low. Experiments prove that the method in this paper uses the features of hearing system in a better way, and the modeling is reasonable and efficient. Both the objective compare of SNR and the subjective listening test show the rationality and superiority of the new method.