DiffVQE is presented as the first reproducible diffusion-based AEC model that outperforms Microsoft's DeepVQE in echo/noise control, model size, and computational complexity using URGENT Challenge data.
UTMOS: UTokyo-SaruLab System for V oice- MOS Challenge 2022
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DiffVQE: Hybrid Diffusion Voice Quality Enhancement Under Acoustic Echo and Noise
DiffVQE is presented as the first reproducible diffusion-based AEC model that outperforms Microsoft's DeepVQE in echo/noise control, model size, and computational complexity using URGENT Challenge data.