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

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/