MODEL PROFILE

NVIDIA-NemotronLabs-RE-USE

NVIDIA · NVIDIA-NemotronLabs-RE-USE

NVIDIA NemotronLabs RE-USE is a 9.6-million-parameter **multilingual universal speech enhancement (USE)** model designed to restore speech quality across a wide range of real-world degradations while preserving speech fidelity. It has the following desirable properties: - Robustness to **diverse degradations**, including additive noise, reverberation, clipping, bandwidth limitation, codec artifacts, packet loss and low-quality mics. - Support for **multiple input sampling rates**, including 8, 16, 22.05, 24, 32, 44.1, and 48 kHz. - Strong **language-agnostic** capability, enabling effective performance across different languages. - If better laughter preservation is desired, please use: NVIDIA-NemotronLabs-RE-USE-laughter. (Note: For overlapping speech, this model is trained to preserve the main speaker while suppressing other speakers.) Comparison with other open-source USE models on the (subsets) of the URGENT 2025 non-blind test set, referenced against original anechoic clean speech.

Audio processinglicense:openmdw-1.1
Context windowNot disclosed
Input → OutputAudio → Audio
Model weightsNot verified
Profile updated2026/11/2 19:15:50
OVERVIEW

Model overview

NVIDIA NemotronLabs RE-USE is a 9.6-million-parameter **multilingual universal speech enhancement (USE)** model designed to restore speech quality across a wide range of real-world degradations while preserving speech fidelity. It has the following desirable properties: - Robustness to **diverse degradations**, including additive noise, reverberation, clipping, bandwidth limitation, codec artifacts, packet loss and low-quality mics. - Support for **multiple input sampling rates**, including 8, 16, 22.05, 24, 32, 44.1, and 48 kHz. - Strong **language-agnostic** capability, enabling effective performance across different languages. - If better laughter preservation is desired, please use: NVIDIA-NemotronLabs-RE-USE-laughter. (Note: For overlapping speech, this model is trained to preserve the main speaker while suppressing other speakers.) Comparison with other open-source USE models on the (subsets) of the URGENT 2025 non-blind test set, referenced against original anechoic clean speech.

Key features

特点摘要待依据来源补齐,不凭模型名称推断能力。

Limitations & considerations

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PRICING & COST

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INDEPENDENT BENCHMARKS

Public benchmarks & run configuration

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Sources & traceability

许可证:openmdw-1.1。模型介绍与第三方评测均以原来源的具体版本和方法为准。