Transcribe audio into text and subtitle files using the local Whisper CLI.
npx skills add https://github.com/kcns008/clusterclaw --skill openai-whisper-kcns008
Please help me install this Agent Skill. Skill: openai-whisper Source: https://github.com/kcns008/clusterclaw/tree/main/skills/openai-whisper Command: npx skills add https://github.com/kcns008/clusterclaw --skill openai-whisper-kcns008
It turns spoken audio into accurate text without sending files to an external API, making transcription faster, private, and easy to automate.
Use the Whisper CLI to transcribe your audio file locally and choose the output format you need.
High-intent search queries and answers about installing and using this skill.
You can transcribe audio to text locally without an API key by using the Whisper CLI. This skill processes audio files offline on your own machine, requiring only an installed whisper binary and downloaded models to generate accurate text outputs.
Yes, you can translate spoken language while transcribing audio files. The local Whisper CLI supports speech-to-text translation workflows, allowing you to convert spoken audio into text in another language simultaneously during offline processing.
Yes, you need to install a whisper binary and download models to use this transcription skill. Because it processes audio locally without an API key, having the necessary models downloaded beforehand is required for offline speech-to-text execution.
The best way to generate subtitle files from interviews and meetings is using the local Whisper CLI. It converts your audio recordings into flexible output formats, including subtitle files, enabling easy editing, publishing, or archiving directly on your machine.
Yes, offline speech-to-text works for processing podcasts and voice notes. The local Whisper CLI transcribes these audio recordings into text without sending files to an external API, making the process faster, private, and easy to automate.
A limitation of transcribing audio without an external API is the local processing requirement. You must have an installed whisper binary and sufficient storage for downloaded models on your machine to process audio files offline for speech-to-text tasks.
mangiapanejohn-devTranscribe audio files to text locally using the Whisper CLI.
bobvarkeyTranscribe audio files into text locally using the Whisper CLI.
DharambirAgrawalTranscribe audio files into text using the OpenAI Whisper API.
MOODMNKY-LLCConverts text to speech offline using sherpa-onnx runtime and voice models.
