Transcribe audio files to text locally using the Whisper CLI.
npx skills add https://github.com/clsdavid/autocrab --skill openai-whisper-clsdavid
Please help me install this Agent Skill. Skill: openai-whisper Source: https://github.com/clsdavid/autocrab/tree/main/skills/openai-whisper Command: npx skills add https://github.com/clsdavid/autocrab --skill openai-whisper-clsdavid
This Skill provides a local, privacy-focused solution for transcribing audio files into text without relying on external APIs or requiring an API key.
txt) and subtitles (srt).Use whisper to transcribe the audio file located at /path/to/audio.mp3 using the medium model and output the result as text.
High-intent search queries and answers about installing and using this skill.
To transcribe audio locally without external APIs, use the Whisper CLI to process audio files directly on your machine. This privacy-focused approach converts speech to text without requiring an API key, outputting plain text or SRT subtitle files.
Yes, you can generate SRT subtitles from voice notes using local speech-to-text. By running the Whisper CLI on your machine, you can process audio inputs and specify SRT as the output format to create subtitle files.
No, you do not need an API key to transcribe meeting recordings into text. This local transcription solution processes audio files directly on your hardware using the Whisper CLI, ensuring data privacy without external API dependencies.
The best way to transcribe video audio for text-based analysis is using the Whisper CLI. It performs local speech-to-text transcription on your machine, supporting various audio input formats and outputting text files for easy searching and summarization.
Yes, local transcription works with the Whisper CLI for meeting recordings. It processes audio files directly on your machine, requiring only the Whisper executable, and supports output formats like TXT and SRT for generating searchable text transcripts.
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