A FreeVC-style conditional VAE with mHuBERT-147 discrete units, mixed-style layer normalization, an augmentation similarity loss, and F0 cross-attention reports better emotion transfer and less source leakage than three baselines, at the cost of a higher word error rate.
Conventional VC models perform well in replicating speaker identity but struggle when the target speech is highly expressive
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Towards Better Disentanglement in Non-Autoregressive Zero-Shot Expressive Voice Conversion
A FreeVC-style conditional VAE with mHuBERT-147 discrete units, mixed-style layer normalization, an augmentation similarity loss, and F0 cross-attention reports better emotion transfer and less source leakage than three baselines, at the cost of a higher word error rate.