How do I install the Whisper Stt skill?

Run npx skillmds@latest add dvcrn/whisper-stt in your terminal (requires Node.js), paste this page's agent-chat prompt into Claude, Cursor, or any MCP-connected agent, or download the SKILL.md file and copy it into your agent's skills directory.

Is Whisper Stt safe to use?

This skill has not completed SkillMD's automated safety review yet. Independent scanners report: SkillSpector: PASS, Skill Scanner: PASS. Capability flags: executes scripts, makes network calls. SkillMD never runs a skill's scripts for you; review the SKILL.md before installing.

Which AI agents work with Whisper Stt?

This skill is tagged as working with Claude Code, Claude.ai, OpenAI Codex. SKILL.md is an open format, so most agents that read a skills directory can load it too.

Is Whisper Stt free to use?

Yes. Installing skills from SkillMD is free, and the skill stays under its author's original license.

Who published Whisper Stt?

dvcrn (@dvcrn) published this skill. Their other Agent Skills are listed on their SkillMD profile.

Whisper Stt by dvcrn — Agent Skill

Name: Whisper Stt
Rating: 4.666666666666667 (3 reviews)
Author: dvcrn

Whisper Stt

Free local speech-to-text transcription using OpenAI Whisper. Transcribe audio files (mp3, wav, m4a, ogg, etc.) to text without API costs. Use when: (1) User needs audio/video transcription, (2) Converting voice memos to text, (3) Generating subtitles (SRT/VTT), (4) Free local STT without cloud API costs.

dvcrn Updated Sep 8, 2026 32 repo stars

File contents

Whisper STT Skill

Free, local speech-to-text using OpenAI Whisper.

Prerequisites

Install dependencies (one-time setup):

pip install openai-whisper torch

Optional: Install ffmpeg for broader format support:

macOS: brew install ffmpeg
Ubuntu: sudo apt install ffmpeg

Usage

Transcribe an audio file

python ~/.openclaw/skills/whisper-stt/scripts/transcribe.py <audio_file>

Options

Option	Description
`--model`	Model size: tiny, base, small, medium, large, large-v3-turbo (default: base)
`--language, -l`	Language code: zh, en, ja, etc. (auto-detect if not specified)
`--output, -o`	Output format: json, txt, srt, vtt (default: json)

Examples

Chinese audio to text:

python ~/.openclaw/skills/whisper-stt/scripts/transcribe.py recording.m4a --language zh --output txt

Generate subtitles (SRT):

python ~/.openclaw/skills/whisper-stt/scripts/transcribe.py video.mp4 --output srt > subtitles.srt

Use faster model:

python ~/.openclaw/skills/whisper-stt/scripts/transcribe.py audio.mp3 --model tiny --output txt

High accuracy (slower):

python ~/.openclaw/skills/whisper-stt/scripts/transcribe.py audio.mp3 --model large-v3 --output txt

Model Selection Guide

Model	Speed	Accuracy	VRAM/RAM	Best For
tiny	~32x	Basic	~1GB	Quick tests, low resource
base	~16x	Good	~1GB	Balanced speed/accuracy
small	~6x	Better	~2GB	Better accuracy
medium	~2x	Very Good	~5GB	High accuracy
large	1x	Excellent	~10GB	Best quality
large-v3-turbo	~8x	Excellent	~6GB	Fast + accurate (recommended)

Troubleshooting

"ModuleNotFoundError: No module named 'whisper'" → Run: pip install openai-whisper torch

"ffmpeg not found" → Install ffmpeg or convert audio to WAV format first

Slow transcription → Use smaller model (tiny/base) or ensure GPU is available (Apple Silicon MPS, NVIDIA CUDA)

Poor accuracy on Chinese → Use --language zh explicitly and consider larger model (medium/large)

Output Formats

json: Full result with segments, timestamps, and metadata
txt: Plain text transcription only
srt: SubRip subtitle format with timing
vtt: WebVTT subtitle format for web players

Credits

---name: whisper-sttdescription: Free local speech-to-text transcription using OpenAI Whisper. Transcribe audio files (mp3, wav, m4a, ogg, etc.) to text without API costs. Use when: (1) User needs audio/video transcription, (2) Converting voice memos to text, (3) Generating subtitles (SRT/VTT), (4) Free local STT without cloud API costs.---# Whisper STT SkillFree, local speech-to-text using OpenAI Whisper.## PrerequisitesInstall dependencies (one-time setup):```bashpip install openai-whisper torch```Optional: Install ffmpeg for broader format support:- macOS: `brew install ffmpeg`- Ubuntu: `sudo apt install ffmpeg`## Usage### Transcribe an audio file```bashpython ~/.openclaw/skills/whisper-stt/scripts/transcribe.py <audio_file>```### Options| Option | Description ||--------|-------------|| `--model` | Model size: tiny, base, small, medium, large, large-v3-turbo (default: base) || `--language, -l` | Language code: zh, en, ja, etc. (auto-detect if not specified) || `--output, -o` | Output format: json, txt, srt, vtt (default: json) |### Examples**Chinese audio to text:**```bashpython ~/.openclaw/skills/whisper-stt/scripts/transcribe.py recording.m4a --language zh --output txt```**Generate subtitles (SRT):**```bashpython ~/.openclaw/skills/whisper-stt/scripts/transcribe.py video.mp4 --output srt > subtitles.srt```**Use faster model:**```bashpython ~/.openclaw/skills/whisper-stt/scripts/transcribe.py audio.mp3 --model tiny --output txt```**High accuracy (slower):**```bashpython ~/.openclaw/skills/whisper-stt/scripts/transcribe.py audio.mp3 --model large-v3 --output txt```## Model Selection Guide| Model | Speed | Accuracy | VRAM/RAM | Best For ||-------|-------|----------|----------|----------|| tiny | ~32x | Basic | ~1GB | Quick tests, low resource || base | ~16x | Good | ~1GB | Balanced speed/accuracy || small | ~6x | Better | ~2GB | Better accuracy || medium | ~2x | Very Good | ~5GB | High accuracy || large | 1x | Excellent | ~10GB | Best quality || large-v3-turbo | ~8x | Excellent | ~6GB | Fast + accurate (recommended) |## Troubleshooting**"ModuleNotFoundError: No module named 'whisper'"**→ Run: `pip install openai-whisper torch`**"ffmpeg not found"**→ Install ffmpeg or convert audio to WAV format first**Slow transcription**→ Use smaller model (tiny/base) or ensure GPU is available (Apple Silicon MPS, NVIDIA CUDA)**Poor accuracy on Chinese**→ Use `--language zh` explicitly and consider larger model (medium/large)## Output Formats- **json**: Full result with segments, timestamps, and metadata- **txt**: Plain text transcription only- **srt**: SubRip subtitle format with timing- **vtt**: WebVTT subtitle format for web players## CreditsPowered by [OpenAI Whisper](https://github.com/openai/whisper) - open source speech recognition.

Frequently asked questions