Transcribe audio files locally using the OpenAI Whisper CLI.
npx skills add https://github.com/robertwaltos/openclaw --skill openai-whisper-robertwaltos
Please help me install this Agent Skill. Skill: openai-whisper Source: https://github.com/robertwaltos/openclaw/tree/main/skills/openai-whisper Command: npx skills add https://github.com/robertwaltos/openclaw --skill openai-whisper-robertwaltos
This Skill provides a local, privacy-focused solution for converting spoken audio into written text, eliminating the need for cloud-based APIs and associated costs or data concerns.
.txt) or subtitle formats (.srt).Use whisper to transcribe the audio file located at /path/to/your/audio.mp3 using the medium model and save the output 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 OpenAI Whisper CLI. This offline audio processing approach eliminates cloud API costs and prevents sensitive audio data from being uploaded to external servers.
Offline speech-to-text transcription supports various audio input formats for processing. The Whisper CLI can output the resulting transcriptions as plain text files or subtitle formats, making it suitable for meeting recordings, voice notes, and interviews.
Yes, local audio transcription requires the Whisper binary to be installed and accessible in your system's PATH. This prerequisite allows the system to execute offline speech-to-text processing commands directly on your machine.
To transcribe audio locally, use the Whisper CLI to specify your audio file path and select a model, such as the medium model. The command processes the audio offline and saves the output as a text file.
Generating subtitle files offline is achieved by running local speech-to-text transcription with the Whisper CLI. This method processes audio files directly on your machine and can output the results in subtitle formats for your recordings.
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