# Amphion — Open-Source Audio, Music, and Speech Generation Toolkit

> A comprehensive research toolkit covering text-to-speech, singing voice synthesis, voice conversion, and music generation with reproducible implementations.

## Install

Save as a script file and run:

# Amphion — Open-Source Audio, Music & Speech Generation Toolkit

## Quick Use
```bash
git clone https://github.com/open-mmlab/Amphion.git
cd Amphion
pip install -r requirements.txt
python bins/tts/inference.py --config egs/tts/VALLE/exp_config.json --text "Hello world"
```

## Introduction
Amphion is an open-source toolkit from OpenMMLab for audio, music, and speech generation research. It provides unified, reproducible implementations of methods spanning TTS, singing voice synthesis, voice conversion, and music generation under a single framework.

## What Amphion Does
- Implements multiple TTS architectures including VALL-E and NaturalSpeech2
- Supports singing voice synthesis and conversion pipelines
- Provides music generation via MaskGCT and related models
- Includes vocoders like BigVGAN and HiFi-GAN for waveform synthesis
- Offers standardized evaluation metrics for audio quality benchmarking

## Architecture Overview
Amphion organizes models into task-specific modules (TTS, SVC, music) that share common components: feature extractors, encoders, decoders, and vocoders. Each model follows a config-driven pattern where YAML files specify architecture, data processing, and training hyperparameters, making experiments reproducible and comparable.

## Self-Hosting & Configuration
- Requires Python 3.9+ with PyTorch and CUDA
- Install all dependencies via the provided requirements file
- Download pre-trained models from Hugging Face model cards
- Configure experiments by editing YAML files in the egs/ directory
- Single-GPU inference; multi-GPU training supported via DDP

## Key Features
- Unified framework covering speech, singing, and music generation
- Reproducible implementations of state-of-the-art methods
- Comprehensive evaluation suite with objective metrics
- Modular vocoder support for plug-and-play waveform synthesis
- Active maintenance by the OpenMMLab research team

## Comparison with Similar Tools
- **Coqui TTS** — focused on TTS deployment; Amphion covers a broader audio research scope
- **ESPnet** — established toolkit; Amphion adds music generation and newer architectures
- **Bark** — consumer-oriented; Amphion targets research reproducibility
- **AudioCraft** — Meta's toolkit; Amphion provides more TTS model variety

## FAQ
**Q: Is Amphion suitable for production TTS deployment?**
A: It is primarily a research toolkit; production use requires additional engineering.

**Q: Which TTS model should I start with?**
A: VALL-E offers a good balance of quality and ease of setup for zero-shot TTS.

**Q: Can I train on my own audio dataset?**
A: Yes, data processing scripts and training configs accept custom datasets.

**Q: What audio formats are supported?**
A: WAV is the primary format; other formats are converted internally via ffmpeg.

## Sources
- https://github.com/open-mmlab/Amphion
- https://amphion.space/

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