speech-enhancement

NVIDIA released NemotronLabs RE-USE, a 9.6M-parameter multilingual universal speech enhancement model that restores speech quality across diverse degradations and sampling rates, outperforming larger open-source USE models while being ready for commercial use.

该论文提出了一个修正的语音质量预测器可攻击性测量协议（包括正确的神经编解码器往返参照和多种子最坏情况评估），并在此基准下发现NISQA、SSL-MOS、DNSMOS和UTMOS在可攻击性上差异巨大（90%至6%），同时揭示了封闭式攻击-检测-补丁循环的局限性。

UniSE is a unified, prompt-free, autoregressive speech enhancement model based on a decoder-only language model, supporting multiple tasks like speech restoration, target speaker extraction, and speech separation in a single model.

A universal speech enhancement model that allows configurable control over both algorithmic and computational latency via parallel convolutions and early-exit mechanisms, enabling a single model to serve diverse real-time applications without retraining.