據 AlphaMoat 統計,截至 2026-09,Elevenlabs Transcribe 累計下載 3,766 次、獲 2 個星標,在全部 5,078 個 AI 技能中排名第 2,826 位,在「設計創意」分類(512 個)中排名第 260 位。
| 平台 | 累計安裝 | 累計下載 | 星標 | 評論 |
|---|---|---|---|---|
| ClawHub ↗ | 121 | 3766 | 2 | - |
| SkillHub ↗ | 208 | 3764 | 2 | — |
各平台的計數口徑不同,統計時間不一致。
支援批次轉錄、透過連結即時處理、麥克風輸入和本地音訊檔案。
資料釋出於 2026-10-27
以下是根據技能文件生成的示例,不代表實際執行結果。
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 | 3766 | — | 2 |
| 2026-08 | 3609 | +5.0% | 2 |
| 2026-07 | 3437 | +8.5% | 2 |
| 2026-06 | 3167 | +4.8% | 2 |
| 2026-05 | 3023 | — | 2 |
| 2026-03 | 2489 | — | 2 |
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。
---
name: elevenlabs-transcribe
description: Transcribe audio to text using ElevenLabs Scribe. Supports batch transcription, realtime streaming from URLs, microphone input, and local files.
homepage: https://elevenlabs.io/speech-to-text
metadata: {"clawdbot":{"emoji":"🎙️","requires":{"bins":["ffmpeg","python3"],"env":["ELEVENLABS_API_KEY"]},"primaryEnv":"ELEVENLABS_API_KEY"}}
---
# ElevenLabs Speech-to-Text
> **Official ElevenLabs skill for speech-to-text transcription.**
Convert audio to text with state-of-the-art accuracy. Supports 90+ languages, speaker diarization, and realtime streaming.
## Prerequisites
- **ffmpeg** installed (`brew install ffmpeg` on macOS)
- **ELEVENLABS_API_KEY** environment variable set
- Python 3.8+ (dependencies auto-install on first run)
## Usage
```bash
{baseDir}/scripts/transcribe.sh <audio_file> [options]
{baseDir}/scripts/transcribe.sh --url <stream_url> [options]
{baseDir}/scripts/transcribe.sh --mic [options]
```
## Examples
### Batch Transcription
Transcribe a local audio file:
```bash
{baseDir}/scripts/transcribe.sh recording.mp3
```
With speaker identification:
```bash
{baseDir}/scripts/transcribe.sh meeting.mp3 --diarize
```
Get full JSON response with timestamps:
```bash
{baseDir}/scripts/transcribe.sh interview.wav --diarize --json
```
### Realtime Streaming
Stream from a URL (e.g., live radio, podcast):
```bash
{baseDir}/scripts/transcribe.sh --url https://npr-ice.streamguys1.com/live.mp3
```
Transcribe from microphone:
```bash
{baseDir}/scripts/transcribe.sh --mic
```
Stream a local file in realtime (useful for testing):
```bash
{baseDir}/scripts/transcribe.sh audio.mp3 --realtime
```
### Quiet Mode for Agents
Suppress status messages on stderr:
```bash
{baseDir}/scripts/transcribe.sh --mic --quiet
```
## Options
| Option | Description |
|--------|-------------|
| `--diarize` | Identify different speakers in the audio |
| `--lang CODE` | ISO language hint (e.g., `en`, `pt`, `es`, `fr`) |
| `--json` | Output full JSON with timestamps and metadata |
| `--events` | Tag audio events (laughter, music, applause) |
| `--realtime` | Stream local file instead of batch processing |
| `--partials` | Show interim transcripts during realtime mode |
| `-q, --quiet` | Suppress status messages (recommended for agents) |
## Output Format
### Text Mode (default)
Plain text transcription:
```
The quick brown fox jumps over the lazy dog.
```
### JSON Mode (`--json`)
```json
{
"text": "The quick brown fox jumps over the lazy dog.",
"language_code": "eng",
"language_probability": 0.98,
"words": [
{"text": "The", "start": 0.0, "end": 0.15, "type": "word", "speaker_id": "speaker_0"}
]
}
```
### Realtime Mode
Final transcripts print as they're committed. With `--partials`:
```
[partial] The quick
[partial] The quick brown fox
The quick brown fox jumps over the lazy dog.
```
## Supported Formats
**Audio:** MP3, WAV, M4A, FLAC, OGG, WebM, AAC, AIFF, Opus
**Video:** MP4, AVI, MKV, MOV, WMV, FLV, WebM, MPEG, 3GPP
**Limits:** Up to 3GB file size, 10 hours duration
## Error Handling
The script exits with non-zero status on errors:
- **Missing API key:** Set `ELEVENLABS_API_KEY` environment variable
- **File not found:** Check the file path exists
- **Missing ffmpeg:** Install with your package manager
- **API errors:** Check API key validity and rate limits
## When to Use Each Mode
| Scenario | Command |
|----------|---------|
| Transcribe a recording | `./transcribe.sh file.mp3` |
| Meeting with multiple speakers | `./transcribe.sh meeting.mp3 --diarize` |
| Live radio/podcast stream | `./transcribe.sh --url <url>` |
| Voice input from user | `./transcribe.sh --mic --quiet` |
| Need word timestamps | `./transcribe.sh file.mp3 --json` |
ContextWeave 架構圖一鍵生成
用 Nano Banana Pro 生成或編輯圖片的指令碼技能。
用 whisper 命令列工具在本機將音訊轉成文字或進行翻譯。
透過 MCP 服務生成與編輯圖表的技能。
面向介面設計的思路與落地建議技能,覆蓋佈局、互動流程、設計令牌與前端改動。
面向多家影片模型 API 的 AI 影片生成與編排技能。
用 ffmpeg 從影片裡取出畫面幀,或生成便於快速檢視的縮圖。
用本地 Whisper 把音訊檔案轉成文字,模型下載完成後可完全離線執行。
資料月份:2026-09 · 下載/星標/安裝數聚合自公開技能註冊庫(ClawHub、SkillHub),按月更新。口徑說明見資料方法。