CosyAccent: Duration-Controllable Accent Normalization Using Source-Synthesis Training Data

Researchers introduced CosyAccent, a non-autoregressive model for accent normalization that uses synthesized second-language speech as training data while aiming at authentic native speech targets. This approach enhances prosodic naturalness and duration control without degrading content integrity, outperforming models trained on real-world data in preserving original content and achieving more natural outputs.

Read the full article at arXiv cs.AI (Artificial Intelligence)

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