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ClearerVoice-Studio

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What ClearerVoice-Studio is

ClearerVoice-Studio is an open-source toolkit for processing speech with AI models. Its speech tasks include enhancement, separation, super-resolution, and audio-visual target-speaker extraction. The project provides pretrained models for these tasks and scripts for training and fine-tuning them. It also includes SpeechScore, a toolkit for assessing speech quality with intrusive and non-intrusive methods and metrics such as PESQ, DNSMOS, SNR, and SI-SDR. ClearerVoice-Studio processes audio and video in batches. Listed audio formats include WAV, AAC, AC3, AIFF, FLAC, M4A, MP3, OGG, OPUS, WMA, and WEBM; FFmpeg is required for audio codecs beyond WAV. Installation is available through `pip install clearvoice` or from the GitHub repository. At inference time, pretrained models are fetched from Hugging Face, and ModelScope downloads are available as a manual alternative. The repository links to ClearVoice demos on Hugging Face and ModelScope, as well as a SpeechScore demo on Hugging Face. It is released under Apache License, Version 2.0. The maintainers invite questions through repository issues, email, and a DingTalk discussion group. The listed platforms include Linux, macOS, Windows, self-hosted use, and web. GPU usage for the Hugging Face demo is limited; ModelScope has a larger GPU usage quota.

Who it suits

ClearerVoice-Studio suits researchers and developers who want speech-processing models, training scripts, and quality assessment tools, as well as end-users seeking batch audio or video processing. Its open-source license and installation options also suit people who want to work from a repository or install the package with pip.

What it does well

Covers enhancement, separation, super-resolution, and target-speaker extraction.
Pretrained models and training and fine-tuning scripts are provided.
SpeechScore includes intrusive and non-intrusive assessment metrics.
Supports batch processing of audio and video.
Apache License, Version 2.0.
Can be installed with pip or from the repository.

What to know first

FFmpeg is required for audio codecs beyond WAV.
Pretrained models are fetched from Hugging Face during inference unless using the manual ModelScope alternative.
Hugging Face demo GPU usage is limited.

Limits

The Hugging Face demo has limited GPU usage; ModelScope has a larger GPU usage quota. FFmpeg is required to use audio codecs beyond WAV.

Getting started

Open the ClearerVoice-Studio GitHub repository.
Install with `pip install clearvoice` or install from the repository.
Install FFmpeg if you plan to use audio codecs beyond WAV.
Use pretrained models fetched from Hugging Face, or manually download them from ModelScope.
Run batch processing on audio or video, or use a linked demo.

Verdict

Choose ClearerVoice-Studio if you need an open-source toolkit covering several speech tasks, model training, and speech-quality assessment. It supports batch audio and video processing and can be installed with pip or from its repository. For audio formats beyond WAV, FFmpeg is required, and the Hugging Face demo has limited GPU usage.

Questions

Is ClearerVoice-Studio free?

Yes. It is open source and includes an Apache License, Version 2.0.

Which speech tasks does it support?

It supports speech enhancement, speech separation, speech super-resolution, and audio-visual target-speaker extraction.

Which platforms are listed?

The listed platforms are Linux, macOS, Windows, self-hosted, and web.

How can I install it?

Install it with `pip install clearvoice` or install it from the GitHub repository.

Which audio formats does it support?

Listed formats are WAV, AAC, AC3, AIFF, FLAC, M4A, MP3, OGG, OPUS, WMA, and WEBM. FFmpeg is required for codecs beyond WAV.

Where do the pretrained models come from?

Models are fetched from Hugging Face during inference. ModelScope downloads are available as a manual alternative.

Facts from ClearerVoice-Studio's own pages

Additional task: ClearVoice also provides speech super-resolution and audio-visual target speaker extraction. · github.com, 9 Oct 2026
Audio formats: The repository says ClearVoice supports formats including WAV, AAC, AC3, AIFF, FLAC, M4A, MP3, OGG, OPUS, WMA, and WEBM, and requires FFmpeg for audio codecs. · github.com, 9 Oct 2026
Demos: The repository links to ClearVoice demos on Hugging Face and ModelScope, plus a SpeechScore demo on Hugging Face. · github.com, 4 Oct 2026
Installation: ClearVoice can be installed from PyPI with `pip install clearvoice` or installed from the GitHub repository. · github.com, 9 Oct 2026
Integration: The README shows a Python interface that accepts audio or video file paths, directories, or `.scp` lists, and includes a NumPy input-to-output interface. · github.com, 9 Oct 2026
Intended users: The repository describes the toolkit as designed for researchers, developers, and end-users. · github.com, 9 Oct 2026
License: The GitHub repository identifies its license as Apache-2.0. · github.com, 9 Oct 2026
Model downloads: Pretrained models are fetched from Hugging Face during inference, with manual downloads available from ModelScope if automatic downloads fail. · github.com, 9 Oct 2026
Model hosting: Pretrained models are fetched from Hugging Face during inference, with ModelScope downloads offered as a manual alternative. · github.com, 4 Oct 2026
Notable limit: The README says Hugging Face demo GPU usage is limited and ModelScope has a larger GPU usage quota. · github.com, 4 Oct 2026
Platforms: The installation instructions describe FFmpeg setup for Ubuntu/Debian, macOS, and Windows. · github.com, 4 Oct 2026
Pretrained models: The listed pretrained models cover speech enhancement, speech separation, speech super-resolution, and audio-visual target speaker extraction. · github.com, 9 Oct 2026
Purpose: ClearerVoice-Studio is an open-source AI speech-processing toolkit with pretrained models for speech enhancement, separation, and target speaker extraction. · github.com, 9 Oct 2026
Quality assessment: The included SpeechScore toolkit evaluates speech quality using metrics including SNR, PESQ, STOI, DNSMOS, and SI-SDR. · github.com, 9 Oct 2026
Speech tasks: ClearVoice supports speech enhancement, speech separation, speech super-resolution, and audio-visual target-speaker extraction. · github.com, 4 Oct 2026
Support: The maintainers invite users to raise repository issues, email the listed contacts, or join their DingTalk group. · github.com, 9 Oct 2026
Training: The repository provides training and fine-tuning scripts for speech enhancement, separation, super-resolution, and target speaker extraction. · github.com, 9 Oct 2026

Where ClearerVoice-Studio stands on Freedom251

AI Speech Enhancement Software#8 of 35
Runtime Version Managers#8 of 30