---name: speech-to-textdescription: Transcribe audio to text with ElevenLabs Scribe and Whisper models via inference.sh CLI. Models: ElevenLabs Scribe v2 (98%+ accuracy, diarization), Fast Whisper Large V3, Whisper V3 Large. Capabilities: transcription, translation, multi-language, timestamps, speaker diarization, audio event tagging. 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, elevenlabs stt, scribe, eleven labs transcribeallowed-tools: Bash(belt *)---

Install the belt CLI skill: npx skills add belt-sh/cli

Speech-to-Text

Transcribe audio to text via inference.sh CLI.

Quick Start

Requires inference.sh CLI (belt). Install instructions

belt login

belt app run infsh/fast-whisper-large-v3 --input '{"audio": "https://audio.mp3"}'

Available Models

Model	App ID	Best For
ElevenLabs Scribe v2	elevenlabs/stt	98%+ accuracy, diarization, 90+ languages
Fast Whisper V3	infsh/fast-whisper-large-v3	Fast transcription
Whisper V3 Large	infsh/whisper-v3-large	Highest accuracy

Examples

Basic Transcription

belt app run infsh/fast-whisper-large-v3 --input '{"audio": "https://meeting.mp3"}'

With Timestamps

belt app sample infsh/fast-whisper-large-v3 --save input.json

# {
#   "audio": "https://podcast.mp3",
#   "return_timestamps": "sentence"
# }

belt app run infsh/fast-whisper-large-v3 --input input.json

Translation (to English)

belt app run infsh/whisper-v3-large --input '{
  "audio": "https://french-audio.mp3",
  "task": "translate"
}'

From Video

# Extract audio from video first
belt app run infsh/video-audio-extractor --input '{"video_file": "https://video.mp4"}' > audio.json

# Transcribe the extracted audio
belt app run infsh/fast-whisper-large-v3 --input '{"audio": "<audio-url>"}'

Workflow: Video Subtitles

# 1. Transcribe video audio
belt app run infsh/fast-whisper-large-v3 --input '{
  "audio": "https://video.mp4",
  "return_timestamps": "sentence"
}' > transcript.json

# 2. Pass the transcript segments as captions
belt app run infsh/caption-videos --input '{
  "video_file": "https://video.mp4",
  "segments": [{"start": 0.0, "end": 2.5, "text": "<segments-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 transcription
• segments: Timestamped segments (if requested)
• language: Detected language

Related Skills

# ElevenLabs STT (98%+ accuracy, diarization)
npx skills add inference-sh/skills@elevenlabs-stt

# ElevenLabs TTS (reverse direction)
npx skills add inference-sh/skills@elevenlabs-tts

# Full platform skill (all apps)
npx skills add inference-sh/skills@infsh-cli

# 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: belt 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