Name: Speech To Text
Author: Ömer Karışman

據 AlphaMoat 統計,截至 2026-09,Speech To Text 累計下載 4,606 次、獲 0 個星標,在全部 5,078 個 AI 技能中排名第 2,069 位,在「設計創意」分類(512 個)中排名第 201 位。

累計安裝

144

累計下載

4606

星標

全站排名

#2,069

全站前 41% · 「設計創意」前 40%

平台	累計安裝	累計下載	星標	評論
ClawHub ↗	144	4388	-	-
SkillHub ↗	140	4606	-	—

各平台的計數口徑不同,統計時間不一致。

這個技能是做什麼的

輸入音訊或從影片提取的音訊會由託管的 inference.sh 服務處理。結果以 JSON 返回，可包含轉寫文字、可選的時間戳片段和檢測到的語言。安裝路徑包含遠端 CLI 安裝指令碼；使用前應檢查安裝來源並核驗校驗和。僅提交符合資料處理要求的媒體，並在分享或使用轉寫內容前複核識別結果。文件翻譯示例的目標語言為英文，需要 infsh CLI。

資料釋出於 2026-10-29

可以用來做什麼

把會議、訪談或語音備忘錄轉成可檢索文字
為播客或影片音訊生成帶時間戳的字幕素材
將音訊轉寫或翻譯為英文文字

什麼時候用

能夠將音訊交由託管推理服務處理時
需要轉寫文字、語言識別或可選時間戳時
已核驗 CLI 安裝方式，並會複核輸出文字時

示例提示詞

以下是根據技能文件生成的示例,不代表實際執行結果。

為這段已獲准交由託管服務處理的會議錄音生成轉寫審閱清單，並指出應核對的說話內容與時間戳；不要上傳或處理音訊。

月度資料趨勢

累計下載4606

星標-

2026-09 起統計方法調整:同名技能按作者分別統計,並覆蓋全部技能。圖中虛線為調整前的月份,與之後的資料不直接比較,也不計算跨越調整的增長。

月份	累計下載	環比	星標
2026-09	4606	—	-
2026-08	4267	+3.9%	-
2026-07	4107	+8.9%	-
2026-06	3771	+6.4%	-
2026-05	3543	—	-
2026-03	2587	—	-

SKILL.md 原文

以下是作者釋出的原始檔案,按純文字顯示,本站未做修改或稽核;其中的連結不可點選,命令請核實後再執行。抓取於 2026-10-23。

3.9 KB · ClawHub v0.1.5

---
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](https://inference.sh) CLI.

展開全部(共 130 行)

![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