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A one-stop Text-to-Speech WebUI platform integrating multiple TTS models.

MITTypeScript 2.3krsxdalvTTS-WebUI Last Updated: 2025-06-19

TTS-WebUI Project Detailed Introduction

Project Overview

TTS-WebUI is a powerful Text-to-Speech (TTS) Web interface platform developed and maintained by rsxdalv. This project integrates various advanced TTS models into a unified Web interface, providing users with a convenient speech synthesis solution.

Project Address: https://github.com/rsxdalv/TTS-WebUI

Core Features

🎯 Multi-Model Integration

The project integrates over 20 different TTS and audio generation models, including:

Text-to-Speech Models

  • ACE-Step - High-quality speech synthesis
  • Kimi Audio - 7B Instruct Model
  • Piper TTS - Lightweight speech synthesis
  • GPT-SoVITS - GPT-based speech synthesis
  • CosyVoice - Multilingual speech synthesis
  • XTTSv2 - Cross-lingual text-to-speech
  • DIA - Conversational AI voice
  • Kokoro - Emotional speech synthesis
  • OpenVoice - Open-source voice cloning
  • ParlerTTS - Prompt-driven dynamic voice generation
  • StyleTTS2 - Stylized speech synthesis
  • Tortoise - High-quality speech synthesis
  • Bark - Multilingual speech model

Audio Generation Models

  • Stable Audio - Stable audio generation
  • MMS - Multilingual speech recognition
  • MAGNet - Audio generation network
  • AudioGen - Audio content generation
  • MusicGen - Music generation model

Voice Processing Tools

  • RVC - Retrieval-based Voice Conversion
  • Vocos - Improved encoder-decoder
  • Demucs - Audio separation
  • SeamlessM4T - Multimodal translation

🖥️ Dual Interface Design

Gradio Interface

  • Traditional Web interface, easy to use
  • Supports real-time preview and debugging
  • Complete model configuration options

React Interface

  • Modern user experience
  • Responsive design
  • Advanced features and customization options

🔧 Technical Architecture

Frontend Technology

  • React - Modern Web frontend framework
  • Gradio - Rapid prototyping interface for machine learning models

Backend Technology

  • Python - Main programming language
  • PyTorch - Deep learning framework
  • FastAPI - High-performance API framework

Supported Platforms

  • Windows - Fully supported
  • Linux - Fully supported
  • macOS - Basic support (some features limited)

Installation & Deployment

Quick Installation

Automatic Installation (Recommended)

# Download the latest version
wget https://github.com/rsxdalv/tts-webui/archive/refs/heads/main.zip

# Unzip and run
unzip main.zip
cd tts-webui-main

# Windows users
start_tts_webui.bat

# Linux/macOS users
./start_tts_webui.sh

Docker Deployment

# Pull the image
docker pull ghcr.io/rsxdalv/tts-webui:main

# Start using Docker Compose
docker compose up -d

# View logs
docker logs tts-webui

Port Configuration

System Requirements

  • Base Installation Size: Approximately 10.7 GB
  • Per Model: Additional 2-8 GB of space required
  • Python Version: 3.10 (recommended)
  • GPU: NVIDIA CUDA support (optional, CPU can also run but slower)

Main Features

📢 Speech Synthesis

  • Supports multiple languages and dialects
  • Adjustable speech speed, pitch, and volume
  • Supports batch processing of long texts
  • Real-time voice preview

🎵 Music Generation

  • Prompt-based music creation
  • Supports multiple music styles
  • Adjustable music length and complexity

🔄 Voice Conversion

  • Voice cloning technology
  • Voice style transfer
  • Multi-speaker speech synthesis

🔌 API Integration

  • OpenAI compatible API interface
  • Supports SillyTavern integration
  • RESTful API design
  • Batch processing interface

Extension System

Extension Management

The project adopts a modular extension system, allowing users to:

  • Install extensions through the Web interface
  • Manage extensions in batches using the extension manager
  • Customize extension development

Recommended Extensions

  • Kokoro TTS API - OpenAI compatible speech synthesis API
  • ACE-Step - High-quality speech synthesis
  • OpenVoice V2 - Latest version of voice cloning
  • Chatterbox - Conversational speech synthesis

Use Cases

🎙️ Content Creation

  • Podcast production
  • Audiobook
  • Video dubbing
  • Advertisement production

🎮 Game Development

  • Character voice
  • Game narration
  • Multilingual localization

🤖 AI Applications

  • Intelligent assistant
  • Chatbot
  • Voice interaction system

📚 Education and Training

  • Online courses
  • Language learning
  • Accessible reading

Technical Features

🔧 Model Optimization

  • Supports model quantization
  • GPU/CPU adaptive
  • Memory optimization management
  • Batch processing acceleration

🔒 Security

  • Local deployment options
  • Data privacy protection
  • Model permission control

🌐 Compatibility

  • Cross-platform support
  • Multiple audio formats
  • Standard API interface
  • Third-party integration

License Information

Code License

  • Main Codebase: MIT License
  • Dependencies: Each follows its respective license

Model License

  • Bark: MIT License
  • Tortoise: Apache-2.0 License
  • MusicGen: CC BY-NC 4.0
  • AudioGen: CC BY-NC 4.0

Notes

Some dependencies may use non-commercial licenses, please read the relevant license terms carefully before use.

Technical Stack Details

Core Dependencies

# Main dependencies
torch>=2.6.0          # Deep learning framework
gradio==5.5.0          # Web interface framework
transformers           # Pre-trained models
accelerate>=0.33.0     # Model acceleration
ffmpeg-python          # Audio processing

Audio Processing

  • FFmpeg: Audio encoding and decoding
  • librosa: Audio analysis
  • soundfile: Audio file reading and writing
  • torchaudio: PyTorch audio processing

Model Framework

  • Hugging Face Transformers: Pre-trained models
  • ONNX: Model optimization and deployment
  • TensorRT: NVIDIA GPU acceleration

Performance Optimization

🚀 Acceleration Technology

  • GPU Acceleration: CUDA and ROCm support
  • Model Quantization: Reduce memory footprint
  • Batch Processing: Improve throughput
  • Caching Mechanism: Reduce redundant calculations

📊 Performance Metrics

  • Latency: Typically <2 seconds (GPU environment)
  • Throughput: Supports concurrent requests
  • Memory Usage: Configurable memory limits
  • Disk Space: Modular installation saves space

Summary

TTS-WebUI is a comprehensive text-to-speech solution that successfully integrates various advanced AI models into an easy-to-use Web interface. Whether you are an individual creator, a corporate developer, or a researcher, you can find a speech synthesis tool that suits your needs in this project.

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