VieNeu-TTS-v3-Turbo

--- license: apache-2.0 datasets: - pnnbao-ump/VieNeu-TTS-10k-ENVI language: - vi - en pipeline_tag: text-to-speech tags: - voice-cloning - code-switching - podcast - emotion-control - 48khz [](https://github.com/pnnbao97/VieNeu-TTS) [](https://huggingface.co/pnnbao-ump/VieNeu-TTS-v3-Turbo) [](https://discord.gg/yJt8kzjzWZ) **VieNeu-TTS v3 Turbo** is the next generation of Vietnamese TTS — **48 kHz** high-fidelity speech, **instant voice cloning**, built-in **multi-speaker default voices**, inline **emotion cues**, and seamless **bilingual (En–Vi) code-switching**. It is a pure-PyTorch engine running on both **GPU and CPU**, using the **MOSS-Audio-Tokenizer-Nano** codec. > [!NOTE] > **Early access.** v3 Turbo is released for **preview**. It is fast and natural, but some features (notably the emotion cues) are still **experimental**. The full v3 release is coming in the next few weeks. > [!IMPORTANT] > **What's new in v3:** > - **48 kHz audio** — a big jump in fidelity over v2 (24 kHz). > - **Built-in default voices** — each default speaker is addressed by a dedicated speaker token + fixed reference, so the voice is **stable and consistent** with no reference clip needed. > - **Emotion / non-verbal cues** *(experimental)* — drop `[cười]`, `[thở dài]`, `[hắng giọng]` straight into your text. > - **Batched generation** — synthesize many chunks at once (batch size up to 32), including a **multi-speaker conversation** mode that batches the whole script regardless of speaker. > - **Instant Voice Cloning** — still clones a voice from just **3–5 seconds** of audio (cloning is available from v3 onward; v1/v2 do not support it). The **VieNeu-TTS v3 Turbo architecture is an original design by the author, Phạm Nguyễn Ngọc Bảo**, and is **trained from scratch** on ~10,000 hours of English–Vietnamese speech — it is **not** a fine-tune, distillation, or adaptation of any existing TTS model. - **Model architecture & training:** designed and trained from scratch by **Phạm Nguyễn Ngọc Bảo** — https://github.com/pnnbao97 - **Audio codec:** [MOSS-Audio-Tokenizer-Nano](https://huggingface.co/OpenMOSS-Team/MOSS-Audio-Tokenizer-Nano) (OpenMOSS-Team) — 48 kHz neural audio codec. - **Phonemizer:** [sea-g2p](https://github.com/pnnbao97/sea-g2p) — fast Vietnamese/English grapheme-to-phoneme, also by the author. Tác giả: **Phạm Nguyễn Ngọc Bảo** Training high-quality TTS models requires significant GPU resources. If you find this model useful, please consider supporting the development: [](https://buymeacoffee.com/pnnbao) git clone https://github.com/pnnbao97/VieNeu-TTS.git cd VieNeu-TTS - **Option 1: CPU** (minimal, torch-free) — runs **v3 Turbo via ONNX** uv sync - **Option 2: GPU** — **v3 Turbo (PyTorch) + VieNeu-TTS v2 (GPU)** uv sync --group gpu **Start the Web UI:** uv run vieneu-web In the Web UI, pick **"VieNeu-TTS-v3-Turbo (Thử nghiệm)"** as the backbone. You get a **Default voice** tab, a **Voice Cloning** tab, and a **Conversation** tab (batched multi-speaker podcasts). pip install vieneu from vieneu import Vieneu from time import time tts = Vieneu() text = f"""[cười] Trời ơi, cái giọng nó tự nhiên mà nó mượt mà dã man, nghe không khác gì người thật luôn. Giờ thì tha hồ mà quẩy content với cả kho giọng nói đa dạng, đủ mọi sắc thái biểu cảm. Mọi người bật loa lên rồi cùng trải nghiệm thử với mình nhé!""" start_time = time() audio = tts.infer(text) tts.save(audio, "output.wav") end_time = time() print(f"Time taken: {end_time - start_time} seconds") for label, voice_id in tts.list_preset_voices(): print(label, voice_id) audio = tts.infer("Mình là Xuân Vĩnh nè!", voice="Xuân Vĩnh") tts.save(audio, "output_Xuân Vĩnh.wav") > [!TIP] > A **temperature around 0.8** gives the most stable result for v3 Turbo. Higher values add expressiveness but can be less stable. Built-in voices — call them by name via `voice="<name>"`, no reference audio required. For any other voice, use **Voice Cloning** with a short reference clip (`ref_audio="..."`). This model package is distributed under [Apache License 2.0](https://www.apache.org/licenses/LICENSE-2.0), matching the upstream model repository. When you reuse, redistribute, or convert these assets, please keep the license notice and attribution intact for both: - the original project: [pnnbao97/VieNeu-TTS](https://github.com/pnnbao97/VieNeu-TTS) - this Hugging Face package: [pnnbao-ump/VieNeu-TTS-v3-Turbo](https://huggingface.co/pnnbao-ump/VieNeu-TTS-v3-Turbo) If you bundle additional third-party assets, their own licenses still apply as well. @misc{vieneutts2026, title = {VieNeu-TTS v3 Turbo: 48kHz Vietnamese Text-to-Speech with Instant Voice Cloning and Emotion Control}, author = {Pham Nguyen Ngoc Bao}, year = {2026}, publisher = {Hugging Face}, howpublished = {\url{https://huggingface.co/pnnbao-ump/VieNeu-TTS-v3-Turbo}} } **Made with ❤️ for the Vietnamese TTS community**