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---
title: Zen Translator
description: Real-time multimodal translation with voice cloning and lip synchronization — 18 input languages, sub-second latency
---
# Zen Translator
Zen Translator is a real-time multimodal translation pipeline combining speech translation, voice cloning, and lip synchronization. It supports 18 input languages and 10 output languages with sub-second end-to-end latency, 3-second voice cloning to preserve speaker characteristics, and accurate lip synchronization for video dubbing.
## Pipeline Components
| Component | Parameters | Latency |
|-----------|------------|---------|
| Zen Omni (translation) | 30B (3B active MoE) | ~500ms |
| CosyVoice 2.0 (voice cloning) | 0.5B | ~150ms |
| Wav2Lip (lip sync) | ~100M | ~200ms |
| **Total** | — | **under 1 second** |
## Language Support
- **Input** — 18 languages + 6 dialects: English, Chinese, Japanese, Korean, Spanish, French, German, Italian, Portuguese, Russian, Arabic, Hindi, Thai, Vietnamese, Indonesian, Malay, Turkish, Polish, Cantonese, Shanghainese, and more
- **Output** — 10 languages: English, Chinese, Japanese, Korean, Spanish, French, German, Italian, Portuguese, Russian
## Quick Start
```bash
# Install
git clone https://github.com/zenlm/zen-translator.git
cd zen-translator
make install
# Download models (~62GB)
make download
# Translate a video
zen-translate video.mp4 -o translated.mp4 -t spanish
```
## Python API
```python
from zen_translator import TranslationPipeline, TranslatorConfig
config = TranslatorConfig(
target_language="es",
enable_lip_sync=True,
preserve_emotion=True,
)
pipeline = TranslationPipeline(config)
await pipeline.load()
# Translate video
result = await pipeline.translate_video(
video="news_clip.mp4",
output_path="translated.mp4",
)
```
## Voice Cloning
Register a speaker with 3 seconds of reference audio:
```python
# Register speaker
await pipeline.register_speaker(
speaker_id="john_doe",
reference_audio="reference.wav"
)
# Translate with cloned voice
result = await pipeline.translate_audio(
audio="input.wav",
target_lang="es",
speaker_id="john_doe"
)
```
## Real-Time Streaming
```javascript
const ws = new WebSocket('ws://localhost:8000/ws/translate');
ws.send(JSON.stringify({ target_lang: 'es', speaker_id: 'my_voice' }));
ws.send(audioChunk); // Send audio chunks
ws.onmessage = (event) => {
// Receive translated audio chunks
};
```
## Use Cases
- Video dubbing for content localization
- Live conference interpretation
- News anchor translation (domain-specific finetuning included)
- Real-time WebRTC conversation translation
- Broadcast media pipeline automation
## Hardware Requirements
| Model | VRAM | Disk |
|-------|------|------|
| Zen Omni | 16 GB | 60 GB |
| CosyVoice 2.0 | 2 GB | 1 GB |
| Wav2Lip | 2 GB | 500 MB |
| **Total** | **~20 GB** | **~62 GB** |
For smaller deployments:
```bash
make download-quantized # 4-bit Zen Omni (~15GB disk)
```
## REST API
| Endpoint | Method | Description |
|----------|--------|-------------|
| `/translate/audio` | POST | Translate audio file |
| `/translate/video` | POST | Translate video with lip sync |
| `/speakers/register` | POST | Register voice for cloning |
| `/speakers` | GET | List registered speakers |
| `/languages` | GET | Supported languages |
| `/ws/translate` | WS | Real-time streaming |
## Get Started
- [HuggingFace](https://huggingface.co/zenlm/zen-omni)
- [GitHub](https://github.com/zenlm/zen-translator)