🦜 VieNeu-TTS
VieNeu-TTS is an advanced on-device Vietnamese Text-to-Speech (TTS) with instant voice cloning and English–Vietnamese bilingual support. The SDK defaults to VieNeu-TTS v3 Turbo (48 kHz) and the minimal install is torch-free — on CPU it runs entirely on ONNX Runtime.
✨ Key Features
- v3 Turbo, 48 kHz — high-fidelity, natural Vietnamese speech (default).
- Torch-free on CPU — minimal install runs on ONNX Runtime; PyTorch is never imported.
- Built-in default voices — call them by name, no reference clip needed.
- Instant voice cloning — clone any voice from 3–5s of audio.
- Emotion cues (experimental) — drop
[cười],[thở dài],[hắng giọng]into the text. - Bilingual (En–Vi) code-switching, fully offline.
📦 Install
# Minimal, TORCH-FREE — runs v3 Turbo on CPU via ONNX Runtime
pip install vieneu
# Optional: GPU + older backends (v1/v2 PyTorch & GGUF, v3 Turbo on GPU)
pip install "vieneu[gpu]"
🚀 Quick Start (Python SDK)
from vieneu import Vieneu
# Default = v3 Turbo (48 kHz). GPU → PyTorch (auto-detected).
tts = Vieneu()
# 1. Built-in voice by name — no reference needed
print("🔊 Generating speech...")
audio = tts.infer("Xin chào, đây là VieNeu-TTS.", voice="Trúc Ly")
tts.save(audio, "output.wav")
print("✅ Saved to output.wav")
# List the built-in voices
voices = tts.list_preset_voices()
print(f"\n🎙️ {len(voices)} built-in voices available:")
for label, voice_id in voices:
print(f" - {label} ({voice_id})")
# 2. Reading style: "tu_nhien" (natural) | "tin_tuc" (news) | "doc_truyen" (storytelling)
audio = tts.infer("Bản tin sáng nay.", voice="Phạm Tuyên", style="tin_tuc")
# 3. Emotion / non-verbal cues — EXPERIMENTAL: [cười] [thở dài] [hắng giọng]
audio = tts.infer("Nghe hay quá đi [cười].", voice="Trúc Ly")
🦜 Zero-shot Voice Cloning
Clone from a short clip; the reference is auto-denoised and trimmed to ≤ 8s.
from vieneu import Vieneu
tts = Vieneu()
# Clone straight from a 3–8s clip
audio = tts.infer("Chào bạn, đây là giọng của tôi.", ref_audio="path/to/voice.wav", denoise=True)
tts.save(audio, "cloned.wav")
# Save a cloned voice and reuse it by name
tts.add_voice("Giọng của tôi", "path/to/voice.wav")
audio = tts.infer("Câu này dùng giọng đã lưu.", voice="Giọng của tôi")
# Just clean up a clip (no synthesis)
wav, sr = tts.denoise("noisy.wav", out_path="clean.wav")
denoise,add_voice, and cloning require the PyTorch (GPU) engine; built-in voices work everywhere.
Older models (v1 / v2 — requires pip install "vieneu[gpu]")
tts = Vieneu(mode="standard") # v2 GGUF, bilingual, podcast
tts = Vieneu(mode="turbo") # v2 Turbo, fastest
🔬 Model Overview
| Model | Engine | Device | Sample Rate | Features |
|---|---|---|---|---|
| VieNeu-TTS v3 Turbo (default) | ONNX (CPU) / PyTorch (GPU) | CPU/GPU | 48 kHz | Default voices, cloning, emotion cues |
| VieNeu-TTS v2 | PyTorch / GGUF | GPU/CPU | 24 kHz | Bilingual, podcast ([gpu]) |
| VieNeu-TTS v1 | PyTorch | GPU/CPU | 24 kHz | Stable, Vietnamese ([gpu]) |
🤝 Support & Links
- GitHub: pnnbao97/VieNeu-TTS
- Discord: Join our community
Made with ❤️ for the Vietnamese TTS community
1 maintainer
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