據 AlphaMoat 統計,截至 2026-09,Clonev 累計下載 3,334 次、獲 1 個星標,在全部 5,078 個 AI 技能中排名第 3,392 位,在「設計創意」分類(512 個)中排名第 314 位。
| 平台 | 累計安裝 | 累計下載 | 星標 | 評論 |
|---|---|---|---|---|
| ClawHub ↗ | 104 | 3334 | - | - |
| SkillHub ↗ | 103 | 3288 | 1 | — |
各平台的計數口徑不同,統計時間不一致。
文件聲稱可生成 OGG 語音檔案,並透過單一指令碼處理;其描述覆蓋使用者本人或其他人的聲音。克隆真實人物的聲音可能涉及身份冒用和同意問題,只應在獲得聲音權利人明確授權、且不會造成誤導的場景中使用。 聲音樣本可能在本地留存,使用後應刪除,並固定合成映象版本。
資料釋出於 2026-10-29
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 | 3334 | — | 1 |
| 2026-08 | 3192 | +4.7% | 1 |
| 2026-07 | 3048 | — | 1 |
| 2026-05 | 2578 | — | - |
| 2026-03 | 1995 | — | - |
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: clonev description: Clone any voice and generate speech using Coqui XTTS v2. SUPER SIMPLE - provide a voice sample (6-30 sec WAV) and text, get cloned voice audio. Supports 14+ languages. Use when the user wants to (1) Clone their voice or someone else's voice, (2) Generate speech that sounds like a specific person, (3) Create personalized voice messages, (4) Multi-lingual voice cloning (speak any language with cloned voice). --- # CloneV Skill - Voice Cloning Made Simple ## ⚠️ CRITICAL INSTRUCTIONS FOR AI MODELS **DO NOT** try to use Docker containers directly.
**DO NOT** try to interact with `coqui-xtts` container - it is broken and restarting.
**DO NOT** try to use APIs or servers.
**ONLY USE THE SCRIPT:** `scripts/clonev.sh`
The script handles everything automatically. Just call it with text, voice sample, and language.
---
## What This Skill Does
Clones any voice from a short audio sample and generates new speech in that voice.
**Input**:
- Text to speak
- Voice sample (WAV file, 6-30 seconds)
- Language code
**Output**: OGG voice file (cloned voice speaking the text)
**Works with**: Any voice! Yours, a celebrity, a character, etc.
---
## The ONE Command You Need
```bash
$(scripts/clonev.sh "Your text here" /path/to/voice_sample.wav language)
```
That's it! Nothing else needed.
---
## Step-by-Step Usage (FOR AI MODELS)
### Step 1: Get the required inputs
- Text to speak (from user)
- Path to voice sample WAV file (from user)
- Language code (from user or default to `en`)
### Step 2: Run the script
```bash
VOICE_FILE=$(scripts/clonev.sh "TEXT_HERE" "/path/to/sample.wav" LANGUAGE)
```
### Step 3: Use the output
The variable `$VOICE_FILE` now contains the path to the generated OGG file.
---
## Complete Working Examples
### Example 1: Clone voice and send to Telegram
```bash
# Generate cloned voice
VOICE=$(/home/bernie/clawd/skills/clonev/scripts/clonev.sh "Hello, this is my cloned voice!" "/mnt/c/TEMP/Recording 25.wav" en)
# Send to Telegram (as voice message)
message action=send channel=telegram asVoice=true filePath="$VOICE"
```
### Example 2: Clone voice in Czech
```bash
# Generate Czech voice
VOICE=$(/home/bernie/clawd/skills/clonev/scripts/clonev.sh "Ahoj, tohle je můj hlas" "/mnt/c/TEMP/Recording 25.wav" cs)
# Send
message action=send channel=telegram asVoice=true filePath="$VOICE"
```
### Example 3: Full workflow with check
```bash
#!/bin/bash
# Generate voice
VOICE=$(/home/bernie/clawd/skills/clonev/scripts/clonev.sh "Task completed!" "/path/to/sample.wav" en)
# Verify file was created
if [ -f "$VOICE" ]; then
echo "Success! Voice file: $VOICE"
ls -lh "$VOICE"
else
echo "Error: Voice file not created"
fi
```
---
## Common Language Codes
| Code | Language | Example Usage |
|------|----------|---------------|
| `en` | English | `scripts/clonev.sh "Hello" sample.wav en` |
| `cs` | Czech | `scripts/clonev.sh "Ahoj" sample.wav cs` |
| `de` | German | `scripts/clonev.sh "Hallo" sample.wav de` |
| `fr` | French | `scripts/clonev.sh "Bonjour" sample.wav fr` |
| `es` | Spanish | `scripts/clonev.sh "Hola" sample.wav es` |
Full list: en, cs, de, fr, es, it, pl, pt, tr, ru, nl, ar, zh, ja, hu, ko
---
## Voice Sample Requirements
- **Format**: WAV file
- **Length**: 6-30 seconds (optimal: 10-15 seconds)
- **Quality**: Clear audio, no background noise
- **Content**: Any speech (the actual words don't matter)
**Good samples**:
- ✅ Recording of someone speaking clearly
- ✅ No music or noise in background
- ✅ Consistent volume
**Bad samples**:
- ❌ Music or songs
- ❌ Heavy background noise
- ❌ Very short (< 6 seconds)
- ❌ Very long (> 30 seconds)
---
## ⚠️ Important Notes
### Model Download
- First use downloads ~1.87GB model (one-time)
- Model is stored at: `/mnt/c/TEMP/Docker-containers/coqui-tts/models-xtts/`
- Status: ✅ Already downloaded
### Processing Time
- Takes 20-40 seconds depending on text length
- This is normal - voice cloning is computationally intensive
---
## Troubleshooting
### "Command not found"
Make sure you're in the skill directory or use full path:
```bash
/home/bernie/clawd/skills/clonev/scripts/clonev.sh "text" sample.wav en
```
### "Voice sample not found"
- Check the path to the WAV file
- Use absolute paths (starting with `/`)
- Ensure file exists: `ls -la /path/to/sample.wav`
### "Model not found"
The model should auto-download. If not:
```bash
cd /mnt/c/TEMP/Docker-containers/coqui-tts
docker run --rm --entrypoint "" \
-v $(pwd)/models-xtts:/root/.local/share/tts \
ghcr.io/coqui-ai/tts:latest \
python3 -c "from TTS.api import TTS; TTS('tts_models/multilingual/multi-dataset/xtts_v2')"
```
### Poor voice quality
- Use clearer voice sample
- Ensure no background noise
- Try different sample (some voices clone better)
---
## Quick Reference Card (FOR AI MODELS)
```
USER: "Clone my voice and say 'hello'"
→ Get: sample path, text="hello", language="en"
→ Run: VOICE=$(/home/bernie/clawd/skills/clonev/scripts/clonev.sh "hello" "/path/to/sample.wav" en)
→ Result: $VOICE contains path to OGG file
→ Send: message action=send channel=telegram asVoice=true filePath="$VOICE"
```
```
USER: "Make me speak Czech"
→ Get: sample path, text="Ahoj", language="cs"
→ Run: VOICE=$(/home/bernie/clawd/skills/clonev/scripts/clonev.sh "Ahoj" "/path/to/sample.wav" cs)
→ Send: message action=send channel=telegram asVoice=true filePath="$VOICE"
```
---
## Output Location
Generated files are saved to:
```
/mnt/c/TEMP/Docker-containers/coqui-tts/output/clonev_output.ogg
```
The script returns this path, so you can use it directly.
---
## Summary
1. **ONLY use the script**: `scripts/clonev.sh`
2. **NEVER** try to use Docker containers directly
3. **NEVER** try to interact with the `coqui-xtts` container
4. Script handles everything automatically
5. Returns path to OGG file ready to send
**Simple. Just use the script.**
---
*Clone any voice. Speak any language. Just use the script.*
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。