OpenSkillIndex← back to search
claude-code

Learn-skills.dev speech-to-text

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

install
source · Clone the upstream repo
git clone https://github.com/NeverSight/learn-skills.dev
Claude Code · Install into ~/.claude/skills/
T=$(mktemp -d) && git clone --depth=1 https://github.com/NeverSight/learn-skills.dev "$T" && mkdir -p ~/.claude/skills && cp -r "$T/data/skills-md/1nfsh/s/speech-to-text" ~/.claude/skills/neversight-learn-skills-dev-speech-to-text-7fc9bd && rm -rf "$T"
manifest: data/skills-md/1nfsh/s/speech-to-text/SKILL.md
source content

Speech-to-Text

Transcribe audio to text via inference.sh CLI.

Speech-to-Text

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"}'

Available Models

ModelApp IDBest 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 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