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

242 stars

Best use case

speech-to-text is best used when you need a repeatable AI agent workflow instead of a one-off prompt. It is especially useful for teams working in multi. 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

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

Users should expect a more consistent workflow output, faster repeated execution, and less time spent rewriting prompts from scratch.

Practical example

Example input

Use the "speech-to-text" skill to help with this workflow task. Context: 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

Example output

A structured workflow result with clearer steps, more consistent formatting, and an output that is easier to reuse in the next run.

When to use this skill

  • Use this skill when you want a reusable workflow rather than writing the same prompt again and again.

When not to use this skill

  • Do not use this when you only need a one-off answer and do not need a reusable workflow.
  • Do not use it if you cannot install or maintain the related files, repository context, or supporting tools.

Installation

Claude Code / Cursor / Codex

$curl -o ~/.claude/skills/speech-to-text/SKILL.md --create-dirs "https://raw.githubusercontent.com/aiskillstore/marketplace/main/skills/inference-sh-9/speech-to-text/SKILL.md"

Manual Installation

  1. Download SKILL.md from GitHub
  2. Place it in .claude/skills/speech-to-text/SKILL.md inside your project
  3. Restart your AI agent — it will auto-discover the skill

How speech-to-text Compares

Feature / Agentspeech-to-textStandard Approach
Platform SupportNot specifiedLimited / Varies
Context Awareness High Baseline
Installation ComplexityUnknownN/A

Frequently Asked Questions

What does this skill do?

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

Where can I find the source code?

You can find the source code on GitHub using the link provided at the top of the page.

SKILL.md Source

# Speech-to-Text

Transcribe audio to text via [inference.sh](https://inference.sh) CLI.

![Speech-to-Text](https://cloud.inference.sh/u/4mg21r6ta37mpaz6ktzwtt8krr/01jz025e88nkvw55at1rqtj5t8.png)

## Quick Start

```bash
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](https://cli.inference.sh) 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](https://dist.inference.sh/cli/checksums.txt) 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

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

### With Timestamps

```bash
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)

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

### From Video

```bash
# 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

```bash
# 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

```bash
# 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](https://inference.sh/docs/apps/running) - How to run apps via CLI
- [Audio Transcription Example](https://inference.sh/docs/examples/audio-transcription) - Complete transcription guide
- [Apps Overview](https://inference.sh/docs/apps/overview) - Understanding the app ecosystem

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