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Voice Quality Control Using Perceptual Expressions for Statistical Parametric Speech Synthesis Based on Cluster Adaptive Training.

, , and . INTERSPEECH, page 2258-2262. ISCA, (2016)

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Adaptive Training for Voice Conversion Based on Eigenvoices., , , and . IEICE Trans. Inf. Syst., 93-D (6): 1589-1598 (2010)Histogram-based spectral equalization for HMM-based speech synthesis using mel-LSP., , , , and . INTERSPEECH, page 1155-1158. ISCA, (2012)Maximum a posteriori adaptation for many-to-one eigenvoice conversion., , , , and . INTERSPEECH, page 1461-1463. ISCA, (2008)Many-to-many eigenvoice conversion with reference voice., , , and . INTERSPEECH, page 1623-1626. ISCA, (2009)Cross-language voice conversion based on eigenvoices., , , , and . INTERSPEECH, page 1635-1638. ISCA, (2009)Improvements of the One-to-Many Eigenvoice Conversion System., , , and . IEICE Trans. Inf. Syst., 93-D (9): 2491-2499 (2010)Emotional transplant in statistical speech synthesis based on emotion additive model., , , and . INTERSPEECH, page 274-278. ISCA, (2015)Voice Quality Control Using Perceptual Expressions for Statistical Parametric Speech Synthesis Based on Cluster Adaptive Training., , and . INTERSPEECH, page 2258-2262. ISCA, (2016)WaveNeXt: ConvNeXt-Based Fast Neural Vocoder Without ISTFT layer., , , , and . ASRU, page 1-8. IEEE, (2023)An evaluation of many-to-one voice conversion algorithms with pre-stored speaker data sets., , , , and . SSW, page 107-112. ISCA, (2007)