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

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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

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 transcription - segments: 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

這是一個專注於語音轉文字的實用工具，文件清晰易懂，提供了多種模型選擇和使用場景示例，翻譯、時間戳等功能也比較完整。不過它主要依賴遠端服務呼叫，缺少本地處理能力，且目前功能以文件說明為主，沒有看到程式碼實現。整體來說作為入門指引質量不錯，但功能深度有待加強。