Transcribe audio files to text locally using the Whisper CLI.
npx skills add https://github.com/Yogi-076/Vajrascan.on --skill openai-whisper-yogi-076
Please help me install this Agent Skill. Skill: openai-whisper Source: https://github.com/Yogi-076/Vajrascan.on/tree/main/moltbot/skills/openai-whisper Command: npx skills add https://github.com/Yogi-076/Vajrascan.on --skill openai-whisper-yogi-076
Provides a simple way to transcribe audio to text locally using the Whisper CLI so you can convert recordings without sending data to cloud services or providing API keys.
Transcribe meeting.mp3 to plain text using the medium model and save the result to the current directory.
High-intent search queries and answers about installing and using this skill.
Transcribe audio files locally using the Whisper CLI to convert recordings to text without sending data to cloud services or providing API keys. It processes meeting recordings, interviews, and voice notes entirely offline.
Offline speech-to-text via the Whisper CLI produces plain text, subtitles, or translated transcripts. You can generate subtitle files from meeting recordings and voice notes for integration into documentation pipelines.
Offline transcription requires a locally installed whisper binary and sufficient disk space for model downloads. You can optionally select smaller models for faster processing or larger models for higher accuracy.
Local audio transcription allows model selection to balance speed and accuracy. Choose smaller models for faster, low-resource transcriptions or larger models to achieve higher accuracy for complex speech-to-text tasks.
Local speech-to-text preserves privacy by running Whisper offline without sending data to cloud services. It eliminates the need for API keys while still handling offline transcription tasks like meeting recordings and voice notes.
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