local-whisperLocal speech-to-text using OpenAI Whisper. Runs fully offline after model download. High quality transcription with multiple model sizes.
Install via ClawdBot CLI:
clawdbot install araa47/local-whisperRequires:
Grade Good — based on market validation, documentation quality, package completeness, maintenance status, and authenticity signals.
Generated Feb 24, 2026
Journalists can use Local Whisper to transcribe interviews and press conferences offline, ensuring data privacy and avoiding cloud service costs. It supports multiple languages and timestamps for accurate quoting and editing.
Researchers in social sciences can transcribe qualitative interviews locally, handling sensitive data without internet dependency. The high-quality models like large-v3 provide accurate transcriptions for detailed analysis.
Content creators can generate subtitles and transcripts for podcasts or videos offline, improving accessibility and SEO. The turbo model offers a good balance of speed and quality for efficient workflow.
Legal professionals can transcribe depositions and meetings locally to maintain confidentiality and compliance. The JSON output with timestamps aids in creating precise legal records.
Healthcare providers can transcribe patient consultations offline, ensuring HIPAA compliance and privacy. The quiet mode allows for discreet use during sensitive discussions.
Offer a free basic version with tiny or base models, and charge for premium features like advanced models (e.g., turbo, large-v3), batch processing, or API integrations. Revenue comes from subscription plans for businesses needing high-volume transcription.
Sell licenses for on-premise deployment to organizations requiring offline, secure transcription, such as government or financial institutions. Include setup support, custom integrations, and maintenance contracts for recurring revenue.
Provide a software development kit (SDK) that allows developers to integrate Local Whisper into their applications, such as note-taking apps or video editors. Monetize through per-application licensing or usage-based fees for commercial use.
💬 Integration Tip
Ensure ffmpeg is installed for audio processing, and use the provided uv setup for easy environment management to avoid dependency issues.
Scored Apr 15, 2026
Transcribe audio via OpenAI Audio Transcriptions API (Whisper).
Local speech-to-text with the Whisper CLI (no API key).
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.