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Learning Interpretable Control Dimensions for Speech Synthesis by Using External Data., , , and . INTERSPEECH, page 32-36. ISCA, (2018)Prosodic Representation Learning and Contextual Sampling for Neural Text-to-Speech., , , , , , and . CoRR, (2020)Perception of prosodic variation for speech synthesis using an unsupervised discrete representation of F0., , and . CoRR, (2020)Camp: A Two-Stage Approach to Modelling Prosody in Context., , , , , , , , and . ICASSP, page 6578-6582. IEEE, (2021)Using generative modelling to produce varied intonation for speech synthesis., , and . CoRR, (2019)Ensemble Prosody Prediction For Expressive Speech Synthesis., , , , , , , , , and . ICASSP, page 1-5. IEEE, (2023)Investigating the Robustness of Sequence-to-Sequence Text-to-Speech Models to Imperfectly-Transcribed Training Data., , , and . INTERSPEECH, page 1546-1550. ISCA, (2019)Prosodic Representation Learning and Contextual Sampling for Neural Text-to-Speech., , , , , , and . ICASSP, page 6573-6577. IEEE, (2021)Controlling High-Dimensional Data With Sparse Input., , , and . CoRR, (2023)