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Factored Maximum Penalized Likelihood Kernel Regression for HMM-Based Style-Adaptive Speech Synthesis.

, , and . J. Sel. Topics Signal Processing, 8 (2): 251-261 (2014)

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High Quality Streaming Speech Synthesis with Low, Sentence-Length-Independent Latency., , , , , , , , , and . CoRR, (2021)Cross-Lingual Low Resource Speaker Adaptation Using Phonological Features., , , , , , , and . Interspeech, page 1594-1598. ISCA, (2021)Vibrato Learning in Multi-Singer Singing Voice Synthesis., , , , and . ASRU, page 773-779. IEEE, (2021)Factored Maximum Penalized Likelihood Kernel Regression for HMM-Based Style-Adaptive Speech Synthesis., , and . J. Sel. Topics Signal Processing, 8 (2): 251-261 (2014)Controllable speech synthesis by learning discrete phoneme-level prosodic representations., , , , , , and . Speech Commun., (2023)Predicting phoneme-level prosody latents using AR and flow-based Prior Networks for expressive speech synthesis., , , , , , , and . CoRR, (2022)Fine-grained Noise Control for Multispeaker Speech Synthesis., , , , , , , , , and . INTERSPEECH, page 828-832. ISCA, (2022)SOMOS: The Samsung Open MOS Dataset for the Evaluation of Neural Text-to-Speech Synthesis., , , , , , , , and . INTERSPEECH, page 2388-2392. ISCA, (2022)Factored MLLR Adaptation Algorithm for HMM-based Expressive TTS., , , and . INTERSPEECH, page 975-978. ISCA, (2012)Investigating Content-Aware Neural Text-to-Speech MOS Prediction Using Prosodic and Linguistic Features., , , , , , and . ICASSP, page 1-5. IEEE, (2023)