language:
- en
- es
- fr
- de
- it
- pt
- pl
- tr
- ru
- nl
- cs
- ar
- zh
- ja
- hu
- ko
- hi
pipeline_tag: text-to-speech
tags:
- text-to-speech
- tts
- ggml
- vulkan
- c++
- on-device
license: other
license_name: coqui-public-model-license
license_link: https://coqui.ai/cpml
base_model: coqui/XTTS-v2
ATTS1HG1: High-Performance GGML Implementation of XTTS-v2
ATTS1HG1 is a high-speed, native C++ implementation of the Coqui XTTS-v2 model, utilizing the GGML tensor library. It features a custom integrated HiFiGAN vocoder optimized for Vulkan and CPU inference.
| Source Code & GUI | Base Model | Backend |
|---|---|---|
| GitHub: ATTS1HG1 | Coqui XTTS-v2 | GGML / Vulkan |
🚀 Key Features
- Blazing Fast: Generates audio in < 0.5s on consumer GPUs (RTX 3090) and ~1.0s on CPU.
- Vulkan Support: Fully optimized HiFiGAN vocoder running on Vulkan (compatible with NVIDIA, AMD, Intel iGPUs).
- Lightweight: Native C++ application, no heavy Python dependencies (PyTorch/TensorFlow not required at runtime).
- Multi-Language: Supports 17 languages.
- Voice : Supports 58 speaker (similar to XTTS).
🌍 Supported Languages
The model supports the following 17 languages:
| Code | Language | Native Name |
|---|---|---|
| en | English | English |
| es | Spanish | Español |
| fr | French | Français |
| de | German | Deutsch |
| it | Italian | Italiano |
| pt | Portuguese | Português |
| pl | Polish | Polski |
| tr | Turkish | Türkçe |
| ru | Russian | Русский |
| nl | Dutch | Nederlands |
| cs | Czech | Čeština |
| ar | Arabic | العربية |
| zh | Chinese | 中文 |
| ja | Japanese | 日本語 |
| hu | Hungarian | Magyar |
| ko | Korean | 한국어 |
| hi | Hindi | हिन्दी |
⚡ Performance
Benchmarks based on standard text generation ("Bonjour le monde") using the C++ client:
| Device | Backend | Latency (Total) | Note |
|---|---|---|---|
| NVIDIA RTX 3090 | Vulkan | ~0.47s | 🚀 Recommended |
| Intel iGPU | Vulkan | ~1.40s | Good for laptops |
| CPU (Ryzen/Intel) | CPU (AVX2) | ~1.02s | Solid fallback |
| NVIDIA RTX 3090 | CUDA | ~1.45s | Slower on HiFiGAN due to kernel overhead |
Note: The Vulkan backend is significantly faster for the HiFiGAN part of the pipeline compared to CUDA due to optimized command buffers and reduced kernel launch overhead for small convolutions.
🛠️ Usage
This repository contains the converted .bin / .gguf weights required by the ATTS1HG1 software.
- Download the model files from this repository.
- Clone and compile the software from GitHub:
git clone [https://github.com/abbndz/ATTS1HG1](https://github.com/abbndz/ATTS1HG1) - Load the model in the GUI or CLI and select Vulkan for best performance.
📜 License
This project uses the weights from Coqui XTTS-v2, which is licensed under the Coqui Public Model License (CPML).
- Non-commercial use: You can use this model for personal, educational, and non-commercial projects.
- Commercial use: Requires a license from Coqui (check their repository for details).
The C++ code (inference engine) is available under the MIT License (see GitHub).
Credits: Based on the excellent work by Coqui.ai and the GGML library by ggerganov.