thanhtantran/VieNeu-TTS

Overview

VieNeu-TTS is an advanced on-device Vietnamese Text-to-Speech (TTS) model with instant voice cloning.

Trained on ~1000 hours of high-quality Vietnamese speech, this model represents a significant upgrade from VieNeu-TTS-140h with the following improvements:

• Enhanced pronunciation: More accurate and stable Vietnamese pronunciation
• Code-switching support: Seamless transitions between Vietnamese and English
• Better voice cloning: Higher fidelity and speaker consistency
• Real-time synthesis: 24 kHz waveform generation on CPU or GPU

VieNeu-TTS-1000h delivers production-ready speech synthesis fully offline.

Author: Phạm Nguyễn Ngọc Bảo

Support This Project

Training high-quality TTS models requires significant GPU resources and compute time. If you find this model useful, please consider supporting the development:

Your support helps maintain and improve VieNeu-TTS! 🙏

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Reference Voices

File	Gender	Accent	Description
Bình (nam miền Bắc)	Male	North	Male voice, North accent
Tuyên (nam miền Bắc)	Male	North	Male voice, North accent
Nguyên (nam miền Nam)	Male	South	Male voice, South accent
Sơn (nam miền Nam)	Male	South	Male voice, South accent
Vĩnh (nam miền Nam)	Male	South	Male voice, South accent
Hương (nữ miền Bắc)	Female	North	Female voice, North accent
Ly (nữ miền Bắc)	Female	North	Female voice, North accent
Ngọc (nữ miền Bắc)	Female	North	Female voice, North accent
Đoan (nữ miền Nam)	Female	South	Female voice, South accent
Dung (nữ miền Nam)	Female	South	Female voice, South accent

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Model Architecture

Component	Description
Backbone	Qwen 0.5B (chat-format LM)
Codec	NeuCodec (supports ONNX + quantization)
Output	24 kHz waveform synthesis
Context Window	2048 tokens shared text + speech
Watermark	Enabled
Training Data	VieNeuCodec-dataset + Emilia dataset pretraining

Features

• High-quality Vietnamese speech
• Instant voice cloning (3–5 second reference audio)
• Fully offline
• Runs real-time or faster
• Multi-voice reference support
• Python API + CLI + Gradio

Troubleshooting

Issue	Cause	Solution
Missing libespeak	System dependency	Install eSpeak NG
GPU OOM	VRAM too small	Use CPU or quantized model
Poor voice match	Bad reference sample	Try a clearer reference clip

License

Apache 2.0

Citation

@misc{vieneutts2025,
  title        = {VieNeu-TTS: Vietnamese Text-to-Speech with Instant Voice Cloning},
  author       = {Pham Nguyen Ngoc Bao},
  year         = {2025},
  publisher    = {Hugging Face},
  howpublished = {\url{https://huggingface.co/pnnbao-ump/VieNeu-TTS}}
}

Please also cite the base model:

@misc{neuttsair2025,
  title        = {NeuTTS Air: On-Device Speech Language Model with Instant Voice Cloning},
  author       = {Neuphonic},
  year         = {2025},
  publisher    = {Hugging Face},
  howpublished = {\url{https://huggingface.co/neuphonic/neutts-air}}
}