Abstract
In this chapter, two parametric source modeling methods are proposed for improving the quality of HMM-based speech synthesis. The two methods model the pitch-synchronous residual frames extracted from the excitation signal based on principal component analysis. In the first method, the pitch-synchronous residual frames are parameterized using principal component analysis. Every residual frame is represented using 30 PCA coefficients. In the second method, an analysis of characteristics of the residual frames around GCI is performed using PCA. Based on the analysis, the pitch-synchronous residual frames are decomposed into deterministic and noise components.
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Rao, K.S., Narendra, N.P. (2019). Parametric Approach of Modeling the Source Signal. In: Source Modeling Techniques for Quality Enhancement in Statistical Parametric Speech Synthesis. SpringerBriefs in Speech Technology. Springer, Cham. https://doi.org/10.1007/978-3-030-02759-9_4
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