Comparison
ASRT_SpeechRecognition vs whisper
Verdict
Pick ASRT_SpeechRecognition if aSRT_SpeechRecognition is a Python-powered deep-learning speech-to-text tool for Chinese languages, leveraging Keras and TensorFlow with CNN-CTC algorithms; pick whisper if decisions about Whisper should consider its application in contexts requiring large-scale weak supervision models for speech recognition, especially where robustness is paramount.
Markdown twin · ASRT_SpeechRecognition alternatives · whisper alternatives
GraphCanon updated 2w
vs
Trust & integrity
| Signal | ASRT_SpeechRecognition | whisper |
|---|---|---|
| Maintenance | Slowing (110d since push) As of 3w · github_public_v1 | Active (8d since push) As of 2w · github_public_v1 |
| Provenance | Not a fork · Personal account As of 3w · github_public_v1 | Not a fork · Organization account As of 2w · github_public_v1 |
| OSV dependency advisories | Published findings As of 1mo · osv@v1 | No published findings from this source as of 2026-07-11 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
- ASRT_SpeechRecognition
- A Deep-Learning-Based Chinese Speech Recognition System
- whisper
- Robust Speech Recognition via Large-Scale Weak Supervision
Stars
- ASRT_SpeechRecognition
- 8.4k
- whisper
- 107k
Forks
- ASRT_SpeechRecognition
- 1.9k
- whisper
- 13k
Open issues
- ASRT_SpeechRecognition
- 115
- whisper
- 135
Language
- ASRT_SpeechRecognition
- Python
- whisper
- Python
Adopt for
- ASRT_SpeechRecognition
- ASRT_SpeechRecognition is a Python-powered deep-learning speech-to-text tool for Chinese languages, leveraging Keras and TensorFlow with CNN-CTC algorithms.
- whisper
- Decisions about Whisper should consider its application in contexts requiring large-scale weak supervision models for speech recognition, especially where robustness is paramount.
Persona
- ASRT_SpeechRecognition
- -
- whisper
- -
Runtime
- ASRT_SpeechRecognition
- -
- whisper
- -
License
- ASRT_SpeechRecognition
- GPL-3.0
- whisper
- MIT
Last pushed
- ASRT_SpeechRecognition
- Apr 10, 2026
- whisper
- Jul 28, 2026
Categories
- ASRT_SpeechRecognition
- Speech & Audio
- whisper
- Speech & Audio
Trust and health
Maintenance
- ASRT_SpeechRecognition
- Slowing (36%)
- whisper
- Active (82%)
Days since push
- ASRT_SpeechRecognition
- 110d
- whisper
- 8d
Open issues (now)
- ASRT_SpeechRecognition
- 115
- whisper
- 135
Owner type
- ASRT_SpeechRecognition
- User
- whisper
- Organization
OSV dependency advisories
- ASRT_SpeechRecognition
- Published findings
- whisper
- No published findings from this source as of 2026-07-11
Full report
- ASRT_SpeechRecognition
- Trust report
- whisper
- Trust report
Choose ASRT_SpeechRecognition if…
- License: ASRT_SpeechRecognition is GPL-3.0, whisper is MIT.
- Tags unique to ASRT_SpeechRecognition: asrt, chinese-speech-recognition, cnn, ctc.
- ASRT_SpeechRecognition ships Docker support for self-hosted deployment.
- When specific to Chinese language recognition needs
When NOT to use ASRT_SpeechRecognition
- When non-Chinese speech recognition is required
- For projects needing different deep learning frameworks than TensorFlow and Keras
Choose whisper if…
- License: whisper is MIT, ASRT_SpeechRecognition is GPL-3.0.
- Tags unique to whisper: openai, weak supervision.
- When you need a tool that leverages large-scale weak supervision to improve the accuracy and reliability of speech recognition.
When NOT to use whisper
- In scenarios necessitating real-time processing where delays associated with large-scale model inference cannot be tolerated.
- If your project strictly requires open collaboration licensing terms beyond the permissive nature of MIT license, such as those which enforce sharing improvements back into the original repository.
Explore
Sources
Every stat on this page traces to a dated GitHub sync, license file, enrichment field, or trust scan.
- GitHub stars (nl8590687/ASRT_SpeechRecognition) · observed Jul 30, 2026
- GitHub forks (nl8590687/ASRT_SpeechRecognition) · observed Jul 30, 2026
- Last push (nl8590687/ASRT_SpeechRecognition) · observed Apr 10, 2026
- License file (GPL-3.0) · observed Jul 30, 2026
- Decision facts (enrichment) · observed Jul 17, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
- GitHub stars (openai/whisper) · observed Aug 6, 2026
- GitHub forks (openai/whisper) · observed Aug 6, 2026
- Last push (openai/whisper) · observed Jul 28, 2026
- License file (MIT) · observed Aug 6, 2026
- Decision facts (enrichment) · observed Jul 11, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
GitHub stars on cards: ASRT_SpeechRecognition 8.4k · whisper 107k (synced Jul 30, 2026).
Common questions
- What is the difference between ASRT_SpeechRecognition and whisper?
- ASRT_SpeechRecognition: A Deep-Learning-Based Chinese Speech Recognition System. whisper: Robust Speech Recognition via Large-Scale Weak Supervision. See the comparison table for live GitHub stats and shared categories.
- When should I choose ASRT_SpeechRecognition over whisper?
- Choose ASRT_SpeechRecognition over whisper when License: ASRT_SpeechRecognition is GPL-3.0, whisper is MIT; Tags unique to ASRT_SpeechRecognition: asrt, chinese-speech-recognition, cnn, ctc; ASRT_SpeechRecognition ships Docker support for self-hosted deployment; When specific to Chinese language recognition needs.
- When should I choose whisper over ASRT_SpeechRecognition?
- Choose whisper over ASRT_SpeechRecognition when License: whisper is MIT, ASRT_SpeechRecognition is GPL-3.0; Tags unique to whisper: openai, weak supervision; When you need a tool that leverages large-scale weak supervision to improve the accuracy and reliability of speech recognition.
- When should I avoid ASRT_SpeechRecognition?
- When non-Chinese speech recognition is required For projects needing different deep learning frameworks than TensorFlow and Keras
- When should I avoid whisper?
- In scenarios necessitating real-time processing where delays associated with large-scale model inference cannot be tolerated. If your project strictly requires open collaboration licensing terms beyond the permissive nature of MIT license, such as those which enforce sharing improvements back into the original repository.
- Is ASRT_SpeechRecognition or whisper more popular on GitHub?
- whisper has more GitHub stars (106,740 vs 8,382). Stars measure visibility, not whether either tool fits your constraints.
- Are ASRT_SpeechRecognition and whisper open source?
- Yes - both are open-source projects on GitHub (ASRT_SpeechRecognition: GPL-3.0, whisper: MIT).
- Where can I find alternatives to ASRT_SpeechRecognition or whisper?
- GraphCanon lists graph-backed alternatives at ASRT_SpeechRecognition alternatives and whisper alternatives (ASRT_SpeechRecognition markdown twin, whisper 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, ASRT_SpeechRecognition or whisper?
- ASRT_SpeechRecognition: Slowing. whisper: Active. 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 ASRT_SpeechRecognition and whisper?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: ASRT_SpeechRecognition trust report; whisper trust report.