Comparison
awesome-whisper vs speech_recognition
Verdict
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; pick speech_recognition if speech_recognition is a Python library providing support for speech recognition across multiple engines and APIs.
Markdown twin · awesome-whisper alternatives · speech_recognition alternatives
GraphCanon updated 3w
vs
Trust & integrity
| Signal | awesome-whisper | speech_recognition |
|---|---|---|
| Maintenance | Slowing (134d since push) As of 3w · github_public_v1 | Steady (43d since push) As of 3w · github_public_v1 |
| Provenance | Not a fork · Personal account As of 3w · github_public_v1 | Not a fork · Personal account As of 3w · github_public_v1 |
| OSV dependency advisories | No lockfile (source not queried) As of 1mo · osv@v1 | No lockfile (source not queried) As of 1mo · osv@v1 |
| deps.dev advisories | Not queried deps.dev@v1 | Not queried deps.dev@v1 |
| OpenSSF Scorecard | Not queried openssf-scorecard@v1 | Not queried openssf-scorecard@v1 |
Tagline
- awesome-whisper
- Curated resources for Whisper speech recognition system
- speech_recognition
- Speech recognition module for Python
Stars
- awesome-whisper
- 2.4k
- speech_recognition
- 9.0k
Forks
- awesome-whisper
- 156
- speech_recognition
- 2.4k
Open issues
- awesome-whisper
- 7
- speech_recognition
- 312
Language
- awesome-whisper
- -
- speech_recognition
- Python
Adopt for
- awesome-whisper
- 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.
- speech_recognition
- speech_recognition is a Python library providing support for speech recognition across multiple engines and APIs.
Persona
- awesome-whisper
- -
- speech_recognition
- -
Runtime
- awesome-whisper
- -
- speech_recognition
- -
License
- awesome-whisper
- CC0-1.0
- speech_recognition
- BSD-3-Clause
Last pushed
- awesome-whisper
- Mar 17, 2026
- speech_recognition
- Jun 16, 2026
Categories
- awesome-whisper
- Speech & Audio
- speech_recognition
- Speech & Audio
Trust and health
Maintenance
- awesome-whisper
- Slowing (36%)
- speech_recognition
- Steady (60%)
Days since push
- awesome-whisper
- 134d
- speech_recognition
- 43d
Open issues (now)
- awesome-whisper
- 7
- speech_recognition
- 312
Full report
- awesome-whisper
- Trust report
- speech_recognition
- Trust report
Choose awesome-whisper if…
- License: awesome-whisper is CC0-1.0, speech_recognition is BSD-3-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 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
Choose speech_recognition if…
- License: speech_recognition is BSD-3-Clause, awesome-whisper is CC0-1.0.
- Pricing: The library itself is free and open-source, but costs might arise from using third-party speech recognition services it supports..
- Tags unique to speech_recognition: audio, python, speech-recognition.
- Use when you need an open-source solution with broad engine compatibility, supporting both online and offline modes.
When NOT to use speech_recognition
- Avoid if your project mandates real-time, low-latency processing exclusively, since some of the supported engines might have higher latency.
- Do not use if strict accuracy in speaker diarization is crucial; competing APIs like Recall.ai may offer better speaker identification features.
Explore
Sources
Every stat on this page traces to a dated GitHub sync, license file, enrichment field, or trust scan.
- GitHub stars (sindresorhus/awesome-whisper) · observed Jul 30, 2026
- GitHub forks (sindresorhus/awesome-whisper) · observed Jul 30, 2026
- Last push (sindresorhus/awesome-whisper) · observed Mar 17, 2026
- License file (CC0-1.0) · observed Jul 30, 2026
- Decision facts (enrichment) · observed Jul 17, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
- GitHub stars (Uberi/speech_recognition) · observed Jul 30, 2026
- GitHub forks (Uberi/speech_recognition) · observed Jul 30, 2026
- Last push (Uberi/speech_recognition) · observed Jun 16, 2026
- License file (BSD-3-Clause) · observed Jul 30, 2026
- Decision facts (enrichment) · observed Jul 16, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
GitHub stars on cards: awesome-whisper 2.4k · speech_recognition 9.0k (synced Jul 30, 2026).
Common questions
- What is the difference between awesome-whisper and speech_recognition?
- awesome-whisper: Curated resources for Whisper speech recognition system. speech_recognition: Speech recognition module for Python. See the comparison table for live GitHub stats and shared categories.
- When should I choose awesome-whisper over speech_recognition?
- Choose awesome-whisper over speech_recognition when License: awesome-whisper is CC0-1.0, speech_recognition is BSD-3-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 choose speech_recognition over awesome-whisper?
- Choose speech_recognition over awesome-whisper when License: speech_recognition is BSD-3-Clause, awesome-whisper is CC0-1.0; Pricing: The library itself is free and open-source, but costs might arise from using third-party speech recognition services it supports.; Tags unique to speech_recognition: audio, python, speech-recognition; Use when you need an open-source solution with broad engine compatibility, supporting both online and offline modes.
- 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
- When should I avoid speech_recognition?
- Avoid if your project mandates real-time, low-latency processing exclusively, since some of the supported engines might have higher latency. Do not use if strict accuracy in speaker diarization is crucial; competing APIs like Recall.ai may offer better speaker identification features.
- Is awesome-whisper or speech_recognition more popular on GitHub?
- speech_recognition has more GitHub stars (8,977 vs 2,361). Stars measure visibility, not whether either tool fits your constraints.
- Are awesome-whisper and speech_recognition open source?
- Yes - both are open-source projects on GitHub (awesome-whisper: CC0-1.0, speech_recognition: BSD-3-Clause).
- Where can I find alternatives to awesome-whisper or speech_recognition?
- GraphCanon lists graph-backed alternatives at awesome-whisper alternatives and speech_recognition alternatives (awesome-whisper markdown twin, speech_recognition markdown twin), 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 mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers.
- Which is better maintained, awesome-whisper or speech_recognition?
- awesome-whisper: Slowing. speech_recognition: Steady. 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 awesome-whisper and speech_recognition?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: awesome-whisper trust report; speech_recognition trust report.