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speech-to-text

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. Capabilitie

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安装到 Tokeny（自动）

下载 ZIP
安装"speech-to-text"技能
技能信息：
- 名称: speech-to-text
- 标识: speech-to-text
- 描述: 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. Capabilitie
- 版本: fbe0aa4
下载地址：
https://www.tokeny.space/api/skills/speech-to-text/download
继续

复制上方内容到 Tokeny 客户端并在会话中发送即可自动安装；也可直接 下载 ZIP并拖动到技能窗口安装。

SKILL.md

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

Speech-to-Text

Transcribe audio to text via inference.sh CLI.

Speech-to-Text

Quick Start

Requires inference.sh CLI (belt). Install instructions

belt login

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

Available Models

ModelApp IDBest For
ElevenLabs Scribe v2elevenlabs/stt98%+ accuracy, diarization, 90+ languages
Fast Whisper V3infsh/fast-whisper-large-v3Fast transcription
Whisper V3 Largeinfsh/whisper-v3-largeHighest accuracy

Examples

Basic Transcription

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

With Timestamps

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

# {
#   "audio_url": "https://podcast.mp3",
#   "timestamps": true
# }

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

Translation (to English)

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

From Video

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

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

Workflow: Video Subtitles

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

# 2. Use transcript for captions
belt 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

# 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 store --category audio

Documentation

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