Simultaneous modeling of phonetic and prosodic parameters,and characteristic conversion for HMM-based text-to-speech systems

By 吉村貴克. 2002

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A Survey on Neural Speech Synthesis (2021, methodology): “Statistic parametric synthesis [409, 350, 408, 418, 351] uses three basic modules, where text analysis module converts characters into linguistic features, and acoustic models generate acoustic features from linguistic features (where the target acoustic features are obtained through vocoder analysi”
Adversarial Audio Synthesis (2018, background): “Some of these systems use learning-based approaches such as a hidden Markov models (Yoshimura, 2002; Tokuda et al., 2013), and separately-trained neural networks pipelines (Ling et al.”
A Survey on Audio Diffusion Models: Text To Speech Synthesis and Enhancement in Generative AI (2023, unknown): “statistical parametric speech synthesis (SPSS) was a popular method [115, 116, 132, 133, 137] consisting of three stages.”
A Speech Parameter Generation Algorithm Considering Global Variance for HMM-Based Speech Synthesis (2007, methodology): “It is shown that this method is superior to a spectral enhancement technique with the post-ﬁlter that is widely used for improving the speech quality [9].”