Speech to text
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Transcribe audio to text with Whisper models via inference.sh CLI. Models: Fast Whisper Large V3, Whisper V3 Large. Capabilities: transcription, translation, multi-language, timestamps. Use for: meeting transcription, subtitles, podcast transcripts, voice notes. Triggers: speech to text, transcription, whisper, audio to text, transcribe audio, voice to text, stt, automatic transcription, subtitles generation, transcribe meeting, audio transcription, whisper ai
SKILL.md
3.9 KB, 919 tokens by cl100k_base, as published. Nobody here has run it
Speech-to-Text
Transcribe audio to text via inference.sh CLI.
Quick Start
curl -fsSL https://cli.inference.sh | sh && infsh login
infsh app run infsh/fast-whisper-large-v3 --input '{"audio_url": "https://audio.mp3"}'
Install note: The install script only detects your OS/architecture, downloads the matching binary from
dist.inference.sh, and verifies its SHA-256 checksum. No elevated permissions or background processes. Manual install & verification available.
Available Models
| Model | App ID | Best For |
|---|---|---|
| Fast Whisper V3 | infsh/fast-whisper-large-v3 | Fast transcription |
| Whisper V3 Large | infsh/whisper-v3-large | Highest accuracy |
Examples
Basic Transcription
infsh app run infsh/fast-whisper-large-v3 --input '{"audio_url": "https://meeting.mp3"}'
With Timestamps
infsh app sample infsh/fast-whisper-large-v3 --save input.json
# {
# "audio_url": "https://podcast.mp3",
# "timestamps": true
# }
infsh app run infsh/fast-whisper-large-v3 --input input.json
Translation (to English)
infsh app run infsh/whisper-v3-large --input '{
"audio_url": "https://french-audio.mp3",
"task": "translate"
}'
From Video
# Extract audio from video first
infsh app run infsh/video-audio-extractor --input '{"video_url": "https://video.mp4"}' > audio.json
# Transcribe the extracted audio
infsh app run infsh/fast-whisper-large-v3 --input '{"audio_url": "<audio-url>"}'
Workflow: Video Subtitles
# 1. Transcribe video audio
infsh app run infsh/fast-whisper-large-v3 --input '{
"audio_url": "https://video.mp4",
"timestamps": true
}' > transcript.json
# 2. Use transcript for captions
infsh app run infsh/caption-videos --input '{
"video_url": "https://video.mp4",
"captions": "<transcript-from-step-1>"
}'
Supported Languages
Whisper supports 99+ languages including: English, Spanish, French, German, Italian, Portuguese, Chinese, Japanese, Korean, Arabic, Hindi, Russian, and many more.
Use Cases
- Meetings: Transcribe recordings
- Podcasts: Generate transcripts
- Subtitles: Create captions for videos
- Voice Notes: Convert to searchable text
- Interviews: Transcription for research
- Accessibility: Make audio content accessible
Output Format
Returns JSON with:
text: Full transcriptionsegments: Timestamped segments (if requested)language: Detected language
Related Skills
# Full platform skill (all 150+ apps)
npx skills add inference-sh/skills@inference-sh
# Text-to-speech (reverse direction)
npx skills add inference-sh/skills@text-to-speech
# Video generation (add captions)
npx skills add inference-sh/skills@ai-video-generation
# AI avatars (lipsync with transcripts)
npx skills add inference-sh/skills@ai-avatar-video
Browse all audio apps: infsh app list --category audio
Documentation
- Running Apps - How to run apps via CLI
- Audio Transcription Example - Complete transcription guide
- Apps Overview - Understanding the app ecosystem