openai-whisperLocal speech-to-text with the Whisper CLI (no API key).
Install via ClawdBot CLI:
clawdbot install steipete/openai-whisperInstall OpenAI Whisper (brew):
brew install openai-whisperRequires:
Grade Good — based on market validation, documentation quality, package completeness, maintenance status, and authenticity signals.
Calls external URL not in known-safe list
https://openai.com/research/whisperAudited Apr 16, 2026 · audit v1.0
Generated Feb 25, 2026
Content creators can transcribe podcast episodes locally for accessibility and SEO. This enables generating text versions for websites and subtitles without relying on cloud services.
Researchers transcribe qualitative interviews for analysis while keeping sensitive data offline. This supports data privacy in fields like sociology or market research.
Businesses transcribe internal meetings to create accurate minutes and action items. It helps teams review discussions without manual note-taking.
Video producers translate and transcribe audio for subtitles in multiple languages. This aids in making content globally accessible without API costs.
Legal professionals transcribe depositions and hearings locally for case documentation. It ensures confidentiality and reduces reliance on external services.
Offer the CLI tool for free while charging for advanced features like batch processing or custom model training. Revenue comes from subscriptions for enterprise support and updates.
Provide APIs or plugins that integrate Whisper into existing software platforms. Revenue is generated through licensing fees and per-use charges for high-volume clients.
Offer consulting services to help organizations implement and optimize Whisper for specific needs. Revenue comes from project-based fees and ongoing maintenance contracts.
💬 Integration Tip
Ensure the Whisper CLI is installed via brew and models are cached locally for offline use; test with sample audio files to verify setup before integration.
Scored Apr 16, 2026
Transcribe audio via OpenAI Audio Transcriptions API (Whisper).
ElevenLabs text-to-speech with mac-style say UX.
Local text-to-speech via sherpa-onnx (offline, no cloud)
Speak responses aloud on macOS using the built-in `say` command when user input indicates Voice Wake/voice recognition (for example, messages starting with "User talked via voice recognition on <device>").
Transcribe audio files to text using local Whisper (Docker). Use when receiving voice messages, audio files (.mp3, .m4a, .ogg, .wav, .webm), or when asked to transcribe audio content.
Turn your AI into JARVIS. Voice, wit, and personality — the complete package. Humor cranked to maximum.