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openai-whisper

Transcribe local audio files to text using the Whisper CLI.

67|24|Updated Jan 31, 2026
Search Tags:#transcription#whisper#audio#local#speech-to-text
One-click install
npx skills add https://github.com/openxjarvis/openclaw-python --skill openai-whisper-openxjarvis
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: openai-whisper
Source: https://github.com/openxjarvis/openclaw-python/tree/main/skills/openai-whisper
Command: npx skills add https://github.com/openxjarvis/openclaw-python --skill openai-whisper-openxjarvis

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

This Skill provides a local, API-key-free solution for converting spoken audio into written text.

Core Features & Use Cases

  • Local Transcription: Transcribe audio files directly on your machine without relying on cloud services.
  • Multiple Models: Supports various model sizes (e.g., turbo, medium) for balancing speed and accuracy.
  • Use Case: Transcribe meeting recordings or voice notes into text for easier searching and documentation.

Quick Start

Use whisper to transcribe the audio file located at /path/to/audio.mp3 using the medium model and output the result as plain text.

Frequently Asked Questions about openai-whisper

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I transcribe an audio file locally without using a cloud API?▼

Local speech-to-text transcription can be performed directly on your machine using the Whisper CLI, converting voice recordings and audio messages into written text without requiring an API key.

Do I need an API key to run speech-to-text transcription on my machine?▼

No, you do not need an API key to run speech-to-text transcription. This approach processes audio files locally, requiring only the Whisper binary to be installed and configured for model downloads.

Can I transcribe meeting recordings and podcasts using local speech-to-text?▼

Yes, local speech-to-text is applicable for transcribing meeting recordings, podcasts, and voice messages directly on your machine, providing a local solution for converting spoken audio into searchable text.

How do I balance speed and accuracy when transcribing audio files locally?▼

You can balance speed and accuracy during local transcription by selecting different model sizes in the Whisper CLI, such as the turbo or medium models, to process audio files according to your needs.

What are the prerequisites for running local speech-to-text transcription?▼

The prerequisite for local speech-to-text is installing the Whisper binary and configuring it for model downloads, which allows the transcription process to run entirely on your local machine.

Does local transcription with Whisper support outputting plain text?▼

Yes, local transcription with Whisper supports outputting results as plain text, allowing you to easily document and search through transcribed voice recordings and audio files.

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