axe-playwright vs ClearerVoice-Studio
axe-playwright
github.comClearerVoice-Studio
github.comSide by side
| Figure | axe-playwright | ClearerVoice-Studio |
|---|---|---|
| Price from | Free | — |
| Free plan | Yes | — |
| Free trial | — | — |
| Open source | — | — |
| Web | Yes | Yes |
| Windows | — | Yes |
| macOS | — | Yes |
| Linux | Yes | Yes |
| Self-hosted | — | Yes |
| Plans published | 1 | 0 |
| Spec score · Runtime Version Managers | 8.5 (#2) | 7.6 (#14) |
| License | The repository is distributed under the MIT License. | The GitHub repository identifies its license as Apache-2.0. |
| Purpose | Axe-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
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.
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.