据 AlphaMoat 统计,截至 2026-09,it will help you to send voice messages to your AI Assistant and also can make it talk 累计下载 4,175 次、获 1 个星标,在全部 5,078 个 AI 技能中排名第 2,406 位,在「设计创意」分类(512 个)中排名第 231 位。
| 平台 | 累计安装 | 累计下载 | 星标 | 评论 |
|---|---|---|---|---|
| ClawHub ↗ | 117 | 3,436 | 1 | - |
| SkillHub ↗ | 559 | 4,175 | 1 | — |
各平台的计数口径不同,统计时间不一致。
TTS 出高质量人声,STT 走 Scribe 做转写;stability 越低情绪越强、越高越稳,不指定语言时会自动识别。单语模型只支持英文,密钥配在 ELEVENLABS_API_KEY。选中的文本和音频会发送到 ElevenLabs API。只提交获准外部处理的内容,避免高敏感录音;使用专用 API key,不要在该技能的 .env 中混放其他密钥。
资料发布于 2026-10-27
以下是根据技能文档生成的示例,不代表实际运行结果。
2026-09 起统计方法调整:同名技能按作者分别统计,并覆盖全部技能。图中虚线为调整前的月份,与之后的数据不直接比较,也不计算跨越调整的增长。
| 月份 | 累计下载 | 环比 | 星标 |
|---|---|---|---|
| 2026-09 | 4,175 | — | 1 |
| 2026-08 | 3,650 | +3.4% | 1 |
| 2026-07 | 3,529 | +14.6% | 1 |
| 2026-06 | 3,080 | -3.8% | 1 |
| 2026-05 | 3,200 | — | 1 |
| 2026-03 | 2,875 | — | 1 |
以下是作者发布的原始文件,按纯文本显示,本站未做修改或审核;其中的链接不可点击,命令请核实后再运行。抓取于 2026-10-23。
--- name: elevenlabs-speech description: Text-to-Speech and Speech-to-Text using ElevenLabs AI. Use when the user wants to convert text to speech, transcribe voice messages, or work with voice in multiple languages. Supports high-quality AI voices and accurate transcription. --- # ElevenLabs Speech Complete voice solution — both TTS and STT using one API: - **TTS**: Text-to-Speech (high-quality voices) - **STT**: Speech-to-Text via Scribe (accurate transcription)
## Quick Start
### Environment Setup
Set your API key:
```bash
export ELEVENLABS_API_KEY="sk_..."
```
Or create `.env` file in workspace root.
### Text-to-Speech (TTS)
Convert text to natural-sounding speech:
```bash
python scripts/elevenlabs_speech.py tts -t "Hello world" -o greeting.mp3
```
With custom voice:
```bash
python scripts/elevenlabs_speech.py tts -t "Hello" -v "voice_id_here" -o output.mp3
```
### List Available Voices
```bash
python scripts/elevenlabs_speech.py voices
```
## Using in Code
```python
from scripts.elevenlabs_speech import ElevenLabsClient
client = ElevenLabsClient(api_key="sk_...")
# Basic TTS
result = client.text_to_speech(
text="Hello from zerox",
output_path="greeting.mp3"
)
# With custom settings
result = client.text_to_speech(
text="Your text here",
voice_id="21m00Tcm4TlvDq8ikWAM", # Rachel
stability=0.5,
similarity_boost=0.75,
output_path="output.mp3"
)
# Get available voices
voices = client.get_voices()
for voice in voices['voices']:
print(f"{voice['name']}: {voice['voice_id']}")
```
## Popular Voices
| Voice ID | Name | Description |
|----------|------|-------------|
| `21m00Tcm4TlvDq8ikWAM` | Rachel | Natural, versatile (default) |
| `AZnzlk1XvdvUeBnXmlld` | Domi | Strong, energetic |
| `EXAVITQu4vr4xnSDxMaL` | Bella | Soft, soothing |
| `ErXwobaYiN019PkySvjV` | Antoni | Well-rounded |
| `MF3mGyEYCl7XYWbV9V6O` | Elli | Warm, friendly |
| `TxGEqnHWrfWFTfGW9XjX` | Josh | Deep, calm |
| `VR6AewLTigWG4xSOukaG` | Arnold | Authoritative |
## Voice Settings
- **stability** (0-1): Lower = more emotional, Higher = more stable
- **similarity_boost** (0-1): Higher = closer to original voice
Default: stability=0.5, similarity_boost=0.75
## Models
- `eleven_turbo_v2_5` - Fast, high quality (default)
- `eleven_multilingual_v2` - Best for non-English
- `eleven_monolingual_v1` - English only
## Integration with Telegram
When user sends text and wants voice reply:
```python
# Generate speech
result = client.text_to_speech(text=user_text, output_path="reply.mp3")
# Send via Telegram message tool with media path
message(action="send", media="path/to/reply.mp3", as_voice=True)
```
## Pricing
Check https://elevenlabs.io/pricing for current rates. Free tier available!
## Speech-to-Text (STT) with ElevenLabs Scribe
Transcribe voice messages using ElevenLabs Scribe:
### Transcribe Audio
```bash
python scripts/elevenlabs_scribe.py voice_message.ogg
```
With specific language:
```bash
python scripts/elevenlabs_scribe.py voice_message.ogg --language ara
```
With speaker diarization (multiple speakers):
```bash
python scripts/elevenlabs_scribe.py voice_message.ogg --speakers 2
```
### Using in Code
```python
from scripts.elevenlabs_scribe import ElevenLabsScribe
client = ElevenLabsScribe(api_key="sk-...")
# Basic transcription
result = client.transcribe("voice_message.ogg")
print(result['text'])
# With language hint (improves accuracy)
result = client.transcribe("voice_message.ogg", language_code="ara")
# With speaker detection
result = client.transcribe("voice_message.ogg", num_speakers=2)
```
### Supported Formats
- mp3, mp4, mpeg, mpga, m4a, wav, webm
- Max file size: 100 MB
- Works great with Telegram voice messages (`.ogg`)
### Language Support
Scribe supports 99 languages including:
- Arabic (`ara`)
- English (`eng`)
- Spanish (`spa`)
- French (`fra`)
- And many more...
Without language hint, it auto-detects.
## Complete Workflow Example
**User sends voice message → You reply with voice:**
```python
from scripts.elevenlabs_scribe import ElevenLabsScribe
from scripts.elevenlabs_speech import ElevenLabsClient
# 1. Transcribe user's voice message
stt = ElevenLabsScribe()
transcription = stt.transcribe("user_voice.ogg")
user_text = transcription['text']
# 2. Process/understand the text
# ... your logic here ...
# 3. Generate response text
response_text = "Your response here"
# 4. Convert to speech
tts = ElevenLabsClient()
tts.text_to_speech(response_text, output_path="reply.mp3")
# 5. Send voice reply
message(action="send", media="reply.mp3", as_voice=True)
```
## Pricing
Check https://elevenlabs.io/pricing for current rates:
**TTS (Text-to-Speech):**
- Free tier: 10,000 characters/month
- Paid plans available
**STT (Speech-to-Text) - Scribe:**
- Free tier available
- Check website for current pricing
ContextWeave 架构图一键生成
用 Nano Banana Pro 生成或编辑图片的脚本技能。
用 whisper 命令行在本地把音频转写成文字或做翻译的技能。
通过 MCP 服务生成与编辑图表的技能。
面向界面设计的思路与落地建议技能,覆盖布局、交互流程、设计令牌与前端改动。
面向多家视频模型 API 的 AI 视频生成与编排技能。
用 ffmpeg 从视频里取出画面帧,或生成便于快速查看的缩略图。
用本地 Whisper 把音频文件转成文字,模型下载完成后可完全离线运行。
数据月份:2026-09 · 下载/星标/安装数聚合自公开技能注册库(ClawHub、SkillHub),按月更新。口径说明见数据方法。