Amphion is a comprehensive open-source research toolkit for audio, music, and speech generation, developed by OpenMMLab. It covers multiple generative tasks including text-to-speech (TTS), singing voice conversion (SVC), voice conversion (VC), text-to-audio (TTA), neural audio codecs, and vocoders. The codebase is organized around config-driven experiments (JSON + shell scripts) with modular base classes for trainers, datasets, and inference. It ingests a wide variety of public datasets (LJSpeech, LibriTTS, VCTK, M4Singer, Emilia, etc.) and provides extensive preprocessing pipelines for feature extraction (mel-spectrograms, F0, energy, phonetic alignments, self-supervised features from HuBERT/Whisper). The primary research focus is on high-quality, zero-shot, and controllable generation using architectures like diffusion models, flow matching, GANs, autoregressive transformers, and vector-quantized codecs. The repository also includes evaluation metrics (F0, energy, intelligibility, speaker similarity) and visualization tools (SingVisio). While primarily a research codebase, it includes inference scripts and Gradio demos for practical use. External dependencies include PyTorch, HuggingFace Transformers, WeNet, Descript Audio Codec, and various pretrained models.
This is a Python application and library for singing voice conversion and real-time voice changing, forked from so-vits-svc and rebuilt around PyTorch, PyTorch Lightning, and a Click-based CLI. The actual code provides two user-facing entry points: the `svc` CLI with commands for inference, realtime microphone conversion, dataset preprocessing, training, clustering, and cleanup, and the `svcg` PySimpleGUI desktop application for interactive and realtime inference. Inference loads a HuBERT content encoder from Hugging Face, extracts pitch using CREPE, DIO, Harvest, or Parselmouth, then runs a VITS-style SynthesizerTrn with either HiFi-GAN or MS/MB-iSTFT decoders conditioned on speaker embeddings. Despite fastapi being listed as a dependency, no HTTP API server exists in the source; the project is a desktop/CLI tool, not a web service.