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thuongvv/VieNeu-TTS
VieNeu-TTS is a text-to-speech model from thuongvv. Use it when you need text read aloud. The card lists the license as apache-2.0.
[](https://github.com/pnnbao97/VieNeu-TTS) [](https://huggingface.co/pnnbao-ump/VieNeu-TTS)
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From the Hugging Face model README

📢 Upcoming Release
VieNeu-TTS-1000h is currently in training, using ~1000 hours of high-quality Vietnamese speech combined with English speech data.
This next version will support bilingual voice synthesis (Vietnamese + English) with consistent speaker identity.Expected improvements:
- More accurate and stable Vietnamese pronunciation
- Improved English pronunciation and code-switching
- Higher voice cloning fidelity and speaker consistency
A GGUF version is also planned for the earliest possible release.
Current release: VieNeu-TTS-140h (stable & production-ready)
VieNeu-TTS is an on-device Vietnamese Text-to-Speech (TTS) model with instant voice cloning.
It is fine-tuned from NeuTTS Air and synthesizes natural 24 kHz speech in real time on CPU or GPU.
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! 🙏
Reference Voice (Speaker Example):
<audio controls src="https://cdn-uploads.huggingface.co/production/uploads/68b923a86c86c127a1975eda/Rpw1V6X1px59SWQKn_W9D.wav"></audio>
Input Text:
Trên bầu trời xanh thẳm, những đám mây trắng lửng lờ trôi như những chiếc thuyền nhỏ đang lướt nhẹ theo dòng gió. Dưới mặt đất, cánh đồng lúa vàng rực trải dài tới tận chân trời, những bông lúa nghiêng mình theo từng làn gió.
Generated Output (Cloned Voice):
<audio controls src="https://cdn-uploads.huggingface.co/production/uploads/68b923a86c86c127a1975eda/f40t4ueGqmsGDmNIGcU3J.mpga"></audio>
VieNeu-TTS supports long-form text synthesis (multiple sentences, paragraphs, or entire articles).
For efficient sentence splitting, text normalization, and streaming playback, please refer to the example script in the repository:
🔗 https://github.com/pnnbao97/VieNeu-TTS
Example file: examples/infer_long_text.py
Long-form speech output example:
<audio controls src="https://cdn-uploads.huggingface.co/production/uploads/68b923a86c86c127a1975eda/DY-yTiPIGZw48Cqkb0BqJ.mpga"></audio>
| 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 |
from pathlib import Path
from vieneu_tts import VieNeuTTS
from utils.normalize_text import VietnameseTTSNormalizer
import soundfile as sf
ref_audio = "sample/id_0001.wav"
ref_text = Path("sample/id_0001.txt").read_text(encoding="utf-8")
normalizer = VietnameseTTSNormalizer()
ref_text_norm = normalizer.normalize(ref_text)
tts = VieNeuTTS(
backbone_repo="pnnbao-ump/VieNeu-TTS",
backbone_device="cuda",
codec_repo="neuphonic/neucodec",
codec_device="cuda"
)
ref_codes = tts.encode_reference(ref_audio)
text = "Công nghệ giọng nói đang phát triển rất nhanh."
text_norm = normalizer.normalize(text)
wav = tts.infer(text_norm, ref_codes, ref_text_norm)
sf.write("output.wav", wav, 24000)
python gradio_app.py
Open your browser at http://127.0.0.1:7860.
| File | Gender | Accent |
|---|---|---|
| id_0001 | Male | South |
| id_0002 | Female | South |
| id_0003 | Male | South |
| id_0004 | Female | South |
| id_0005 | Male | South |
| id_0007 | Male | South |
Odd numbers = Male
Even numbers = Female
| 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 |
Apache 2.0
@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}}
}