Transcribe and translate audio files locally using the Whisper CLI.
npx skills add https://github.com/SeanHogg/coderClaw --skill openai-whisper-seanhogg
Please help me install this Agent Skill. Skill: openai-whisper Source: https://github.com/SeanHogg/coderClaw/tree/main/product/skills/openai-whisper Command: npx skills add https://github.com/SeanHogg/coderClaw --skill openai-whisper-seanhogg
This Skill enables local speech-to-text transcription of audio files without requiring an API key, ensuring privacy and offline functionality.
Use whisper to transcribe the audio file located at /path/to/audio.mp3 using the medium model and output the result as a text file.
High-intent search queries and answers about installing and using this skill.
Local speech-to-text transcription can be performed directly on your machine using the Whisper CLI, eliminating the need for an API key. This approach ensures privacy and enables offline functionality for processing audio files.
Yes, audio translation into English can be executed locally using the Whisper CLI. This functionality allows you to translate spoken content from various languages directly on your machine without requiring external API calls.
Yes, the Whisper CLI binary must be installed and accessible in your system's PATH to transcribe meeting recordings. This local setup serves as the foundational requirement for executing the speech-to-text process.
The transcription process supports multiple output formats, including TXT and SRT. This allows you to transcribe voice notes into a text document for easy searching and summarization, depending on your required format.
To start local transcription, you use the Whisper CLI to specify the audio file path, select a model like medium, and define the output format. This executes the speech-to-text task directly on your local machine.
Local audio transcription relies entirely on your machine's processing capabilities and requires the Whisper CLI binary in the system PATH. It is best suited for transcribing voice notes, lectures, and meetings where offline privacy is prioritized.
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