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SEMamba++ significantly improves speech restoration by cleverly integrating frequency-domain inductive biases into a state-space model, outperforming existing methods while maintaining efficiency.
Achieve state-of-the-art speech synthesis with a GAN vocoder that's 88% smaller, thanks to a new training objective that leverages self-supervised learning for better generalization.
