--- title: "whisper-diarization vs awesome-whisper" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/mahmoudashraf97-whisper-diarization-vs-sindresorhus-awesome-whisper" tools: ["mahmoudashraf97-whisper-diarization", "sindresorhus-awesome-whisper"] --- # whisper-diarization vs awesome-whisper *GraphCanon updated Jul 30, 2026* ## Verdict Pick whisper-diarization if automatic Speech Recognition with Speaker Diarization based on OpenAI Whisper for Python projects; pick awesome-whisper if awesome-whisper is an organized repository aggregating resources for OpenAI's Whisper AI-powered speech recognition system, covering models, apps, bindings, packages, and community tools. [whisper-diarization](https://github.com/MahmoudAshraf97/whisper-diarization) reports 5.6k GitHub stars, 503 forks, and 41 open issues, last pushed Feb 23, 2026. [awesome-whisper](https://github.com/sindresorhus/awesome-whisper) has 2.4k stars, 156 forks, and 7 open issues, last pushed Mar 17, 2026. Figures are from public GitHub metadata via [whisper-diarization's repository](https://github.com/MahmoudAshraf97/whisper-diarization) and [awesome-whisper's repository](https://github.com/sindresorhus/awesome-whisper). | | [whisper-diarization](/tools/mahmoudashraf97-whisper-diarization.md) | [awesome-whisper](/tools/sindresorhus-awesome-whisper.md) | | --- | --- | --- | | Tagline | Automatic Speech Recognition with Speaker Diarization based on OpenAI Whisper | Curated resources for Whisper speech recognition system | | Stars | 5,615 | 2,361 | | Forks | 503 | 156 | | Open issues | 41 | 7 | | Language | Jupyter Notebook | - | | Adopt for | Automatic Speech Recognition with Speaker Diarization based on OpenAI Whisper for Python projects | awesome-whisper is an organized repository aggregating resources for OpenAI's Whisper AI-powered speech recognition system, covering models, apps, bindings, packages, and community tools. | | Persona | - | - | | Runtime | - | - | | License | BSD-2-Clause | CC0-1.0 | | Categories | Developer Tools, Speech & Audio | Speech & Audio | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [whisper-diarization](/tools/mahmoudashraf97-whisper-diarization.md) | [awesome-whisper](/tools/sindresorhus-awesome-whisper.md) | | --- | --- | --- | | Days since push | 156d | 134d | | Open issues (now) | 41 | 7 | | Full report | [trust report](/tools/mahmoudashraf97-whisper-diarization/trust.md) | [trust report](/tools/sindresorhus-awesome-whisper/trust.md) | ## Decision facts: whisper-diarization - **Adopt for:** Automatic Speech Recognition with Speaker Diarization based on OpenAI Whisper for Python projects - **License detail:** BSD-2-Clause ## Decision facts: awesome-whisper - **Adopt for:** awesome-whisper is an organized repository aggregating resources for OpenAI's Whisper AI-powered speech recognition system, covering models, apps, bindings, packages, and community tools. ## Choose when ### Choose whisper-diarization if… - License: whisper-diarization is BSD-2-Clause, awesome-whisper is CC0-1.0. - Tags unique to whisper-diarization: asr, speaker-diarization, speech-recognition, whisper. - Also covers Developer Tools. - You need advanced speech recognition capabilities paired with speaker diarization in your Python project. ### Choose awesome-whisper if… - License: awesome-whisper is CC0-1.0, whisper-diarization is BSD-2-Clause. - Tags unique to awesome-whisper: ai, artificial-intelligence, gpt, openai. - When seeking curated information on Whisper variants optimized for various platforms and languages ## When NOT to use whisper-diarization - If your project is restricted to use only open-source tools under the MIT license, as whisper-diarization uses the BSD-2-Clause license. - Your environment cannot support Python 3.10 or later or you lack prerequisites such as Cython and FFMPEG installation rights. ## When NOT to use awesome-whisper - If looking for resources related to speech recognition systems from other providers not listed under OpenAI's Whisper ecosystem - In cases where the focus is on using pre-integrated solutions without the need for model customization ## Common questions ### What is the difference between whisper-diarization and awesome-whisper? whisper-diarization: Automatic Speech Recognition with Speaker Diarization based on OpenAI Whisper. awesome-whisper: Curated resources for Whisper speech recognition system. See the comparison table for live GitHub stats and shared categories. ### When should I choose whisper-diarization over awesome-whisper? Choose whisper-diarization over awesome-whisper when License: whisper-diarization is BSD-2-Clause, awesome-whisper is CC0-1.0; Tags unique to whisper-diarization: asr, speaker-diarization, speech-recognition, whisper; Also covers Developer Tools; You need advanced speech recognition capabilities paired with speaker diarization in your Python project. ### When should I choose awesome-whisper over whisper-diarization? Choose awesome-whisper over whisper-diarization when License: awesome-whisper is CC0-1.0, whisper-diarization is BSD-2-Clause; Tags unique to awesome-whisper: ai, artificial-intelligence, gpt, openai; When seeking curated information on Whisper variants optimized for various platforms and languages. ### When should I avoid whisper-diarization? If your project is restricted to use only open-source tools under the MIT license, as whisper-diarization uses the BSD-2-Clause license. Your environment cannot support Python 3.10 or later or you lack prerequisites such as Cython and FFMPEG installation rights. ### When should I avoid awesome-whisper? If looking for resources related to speech recognition systems from other providers not listed under OpenAI's Whisper ecosystem In cases where the focus is on using pre-integrated solutions without the need for model customization ### Is whisper-diarization or awesome-whisper more popular on GitHub? whisper-diarization has more GitHub stars (5,615 vs 2,361). Stars measure visibility, not whether either tool fits your constraints. ### Are whisper-diarization and awesome-whisper open source? Yes - both are open-source projects on GitHub (whisper-diarization: BSD-2-Clause, awesome-whisper: CC0-1.0). ### Where can I find alternatives to whisper-diarization or awesome-whisper? GraphCanon lists graph-backed alternatives at [whisper-diarization alternatives](/tools/mahmoudashraf97-whisper-diarization/alternatives) and [awesome-whisper alternatives](/tools/sindresorhus-awesome-whisper/alternatives) ([whisper-diarization markdown twin](/tools/mahmoudashraf97-whisper-diarization/alternatives.md), [awesome-whisper markdown twin](/tools/sindresorhus-awesome-whisper/alternatives.md)), ranked by typed relationship edges rather than popularity votes. ### Is there a machine-readable version of this comparison? Yes. The markdown twin at [this comparison](/compare/mahmoudashraf97-whisper-diarization-vs-sindresorhus-awesome-whisper.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, whisper-diarization or awesome-whisper? whisper-diarization: Slowing. awesome-whisper: Slowing. Compare maintenance labels, days since push, and release cadence in the trust section below - stars alone do not measure maintenance. ### Where are the full trust reports for whisper-diarization and awesome-whisper? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [whisper-diarization trust report](/tools/mahmoudashraf97-whisper-diarization/trust); [awesome-whisper trust report](/tools/sindresorhus-awesome-whisper/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=mahmoudashraf97-whisper-diarization`](/api/graphcanon/graph?tool=mahmoudashraf97-whisper-diarization) - LLM index: [/llms.txt](/llms.txt) - Full corpus: [/llms-full.txt](/llms-full.txt) _GraphCanon - The knowledge graph for AI development. https://www.graphcanon.com/_