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axe-playwright vs ClearerVoice-Studio

axe-playwright

github.com

ClearerVoice-Studio

github.com

Side by side

Figureaxe-playwrightClearerVoice-Studio
Price fromFree—
Free planYes—
Free trial——
Open source——
WebYesYes
Windows—Yes
macOS—Yes
LinuxYesYes
Self-hosted—Yes
Plans published10
Spec score · Runtime Version Managers8.5 (#2)7.6 (#14)
LicenseThe repository is distributed under the MIT License.The GitHub repository identifies its license as Apache-2.0.
PurposeAxe-Playwright provides commands to integrate the axe-core accessibility testing engine with Playwright tests.ClearerVoice-Studio is an open-source AI speech-processing toolkit with pretrained models for speech enhancement, separation, and target speaker extraction.

Plans

axe-playwright

  • axe-playwrightFree

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ClearerVoice-Studio

No plans published.

ClearerVoice-Studio pricing →

In their own words

axe-playwright

axe-playwright adds axe-core accessibility checks to Playwright tests. Its commands can inject and configure axe, check a page, retrieve results or violations, and report findings. Checks can cover a whole page document or a selected DOM context such as a selector. Options support axe.run settings, impact filtering, detailed reports, and verbose output; an optional setting logs violations without failing the test. The integration works with Playwright’s Chromium, Firefox, and WebKit browsers. Reporting options include terminal output, a v2 terminal format, HTML, and JUnit. The project shows configurations for WCAG 2.1 AA, WCAG 2.2 AA, best-practice, and EN 301 549 tags, and lists WCAG 2.2 coverage. Installation uses axe-playwright and Playwright as npm development dependencies. axe-core is bundled, so a separate installation is not needed. The package is distributed under the MIT License. It is available for Linux and web, with CI/CD integration. The project says it is not formally affiliated with Deque Systems, though it uses axe-core with permission.

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ClearerVoice-Studio

ClearerVoice-Studio is an open-source toolkit for AI speech processing, aimed at researchers, developers, and end-users. Its tasks include speech enhancement, speech separation, speech super-resolution, and audio-visual target-speaker extraction. The project provides pretrained models for these tasks and scripts for training and fine-tuning. It also includes SpeechScore for intrusive and non-intrusive speech-quality assessment, with metrics including PESQ, DNSMOS, SNR, and SI-SDR. The toolkit processes audio and video in batches and provides a Python interface for file paths, directories, `.scp` lists, and NumPy input-to-output use. Listed audio formats include WAV, AAC, AC3, AIFF, FLAC, M4A, MP3, OGG, OPUS, WMA, and WEBM; FFmpeg is required for codecs beyond WAV. Installation is available through `pip install clearvoice` or from the GitHub repository. Pretrained models are fetched from Hugging Face during inference, with ModelScope downloads available manually. It is released under Apache License, Version 2.0.

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