- name
- speech-to-text
- description
- 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
- allowed-tools
- Bash(infsh *)
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.jsonTranslation (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-videoBrowse 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