Author: Phạm Nguyễn Ngọc Bảo

☕ Support This Project

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

• Windows: Download .msi from eSpeak NG Releases.
• macOS: brew install espeak
• Linux: sudo apt install espeak-ng

🚀 How to Use

Use the source code from GitHub for the best experience with full text preprocessing support:

# 1. Clone repository
git clone https://github.com/pnnbao97/VieNeu-TTS.git
cd VieNeu-TTS

2. Sync environment (requires uv)
uv sync

3. Launch Web UI
uv run gradio_app.py

📦 Using Python SDK (vieneu)

Install the SDK to integrate VieNeu-TTS-0.3B into your research or applications:

# Windows (Avoid llama-cpp build errors)
pip install vieneu --extra-index-url https://pnnbao97.github.io/llama-cpp-python-v0.3.16/cpu/

Linux / MacOS
pip install vieneu

Full Features Guide

from vieneu import Vieneu
import os

Initialization
tts = Vieneu()  # Default: 0.3B-Q4 GGUF for CPU
os.makedirs("outputs", exist_ok=True)

1. List preset voices
availablevoices = tts.listpreset_voices()
for desc, name in available_voices:
    print(f"   - {desc} (ID: {name})")

2. Use specific voice (dynamically select second voice)
if available_voices:
    , myvoiceid = availablevoices[1] if len(availablevoices) > 1 else availablevoices[0]
    voicedata = tts.getpresetvoice(myvoice_id)
    audiospec = tts.infer(text="Chào bạn, tôi đang nói bằng giọng của bác sĩ Tuyên.", voice=voicedata)
    tts.save(audiospec, f"outputs/standard{myvoiceid}.wav")
    print(f"💾 Saved synthesis to: outputs/standard{myvoice_id}.wav")

3. Standard synthesis (uses default voice)
text = "Xin chào, tôi là VieNeu. Tôi có thể giúp bạn đọc sách, làm chatbot thời gian thực, hoặc thậm chí clone giọng nói của bạn."
audio = tts.infer(text=text)
tts.save(audio, "outputs/standard_output.wav")
print("💾 Saved synthesis to: outputs/standard_output.wav")

4. Zero-shot voice cloning
if os.path.exists("examples/audioref/examplengoc_huyen.wav"):
    cloned_audio = tts.infer(
        text="Đây là giọng nói đã được clone thành công từ file mẫu.",
        refaudio="examples/audioref/examplengochuyen.wav",
        ref_text="Tác phẩm dự thi bảo đảm tính khoa học, tính đảng, tính chiến đấu, tính định hướng."
    )
    tts.save(clonedaudio, "outputs/standardcloned_output.wav")
    print("💾 Saved cloned voice to: outputs/standardclonedoutput.wav")

5. Cleanup
tts.close()

📊 Technical Specifications

• Format: GGUF (Q4_0)
• Size: ~200 MB
• Standard Devices: Office laptops, Mini PCs, and computers without GPUs.
• Performance: Achieves real-time speed even on standard consumer CPUs.

⚠️ Licensing & Copyright

• ✅ Free: For students, researchers, and non-profit purposes.
• ⚠️ Commercial/Enterprise: Use for businesses or commercial products is strictly prohibited without prior authorization.
• Commercial Licensing: Please contact the author (Phạm Nguyễn Ngọc Bảo) for licensing terms (Estimated: 5,000 USD/year - negotiable).

📑 Citation

@misc{vieneutts03bgguf2026,
  title        = {VieNeu-TTS-0.3B-GGUF: CPU-Optimized Vietnamese Text-to-Speech},
  author       = {Pham Nguyen Ngoc Bao},
  year         = {2026},
  publisher    = {Hugging Face},
  howpublished = {\url{https://huggingface.co/pnnbao-ump/VieNeu-TTS-0.3B-q4-gguf}}
}