Transcribe audio locally using the Whisper CLI with configurable models and output formats.
npx skills add https://github.com/aresbit/MateBot --skill openai-whisper-aresbit
Please help me install this Agent Skill. Skill: openai-whisper Source: https://github.com/aresbit/MateBot/tree/main/skills/openai-whisper Command: npx skills add https://github.com/aresbit/MateBot --skill openai-whisper-aresbit
This skill enables local transcription of audio using the Whisper CLI without requiring an API key.
whisper /path/audio.mp3 --model medium --output_format txt --output_dir . whisper /path/audio.m4a --task translate --output_format srt
High-intent search queries and answers about installing and using this skill.
To transcribe audio locally without an API key, use the Whisper CLI to process files entirely on-device. It allows configurable model selection and output formats like txt and srt without sending data to external services.
Yes, you can transcribe podcasts and lectures offline on your laptop using Whisper CLI. It caches models locally for on-device processing, making it suitable for personal workflows without internet access.
To translate audio to English text using Whisper, run the CLI with the --task translate option. This generates translated output files in formats such as srt or txt from your original audio input.
For offline transcription, you need to install Whisper via a package manager like brew. Once installed, it operates locally using cached models, requiring no external API keys or active internet connection for transcription tasks.
Local Whisper transcription processes common audio formats like mp3 and m4a, outputting text files such as txt for plain text and srt for subtitles. You configure these via CLI arguments during execution.
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