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Voice conversion can now leverage a unified diffusion model, achieving high naturalness and performer similarity while navigating the complexities of speech and singing.
Context-aware snapping can transform weakly aligned audio-score pairs into high-quality training data, dramatically boosting transcription accuracy.
