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High-Fidelity Speech Synthesis with Minimal Supervision: All Using Diffusion Models
To address these issues, we propose a minimally-supervised high-fidelity speech synthesis method, where all modules are constructed based on the diffusion models.
Learning Speech Representation From Contrastive Token-Acoustic Pretraining
However, existing contrastive learning methods in the audio field focus on extracting global descriptive information for downstream audio classification tasks, making them unsuitable for TTS, VC, and ASR tasks.
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