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Amphion

github.com

Free plan LinuxSelf-hosted
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Spec score 8.7 #26 of 223 in Text-to-Speech Software

Spec sheet

Purpose
Amphion is an open-source toolkit for audio, music, and speech generation intended to support reproducible research and help junior researchers and engineers get started.Read 5 Oct 2026 · github.com
Intended users
The project describes itself as supporting reproducible research and helping junior researchers and engineers enter audio, music, and speech generation research and development.Read 5 Oct 2026 · github.com
Free plan
YesRead 20 Sep 2026 · github.com
License
Amphion is released under the MIT License and is stated to be free for research and commercial use.Read 5 Oct 2026 · github.com
Audio evaluation
Its evaluation metrics cover F0 and energy modeling, intelligibility, spectrogram distortion, and speaker similarity.Read 5 Oct 2026 · github.com
Dataset preprocessing
It unifies preprocessing for multiple open-source audio datasets and supports the Emilia dataset and Emilia-Pipe pipeline for in-the-wild speech data.Read 4 Oct 2026 · github.com
Datasets
Amphion unifies preprocessing for several open-source datasets and supports the Emilia dataset and Emilia-Pipe for in-the-wild speech data.Read 5 Oct 2026 · github.com
Docker requirement
The Docker instructions call for Docker, an NVIDIA Driver, NVIDIA Container Toolkit, and CUDA, and state that mounting the dataset with -v is necessary.Read 5 Oct 2026 · github.com
Export formats
WAVRead 20 Sep 2026 · github.com
External model tools
For content-based features, the README lists pretrained models including WeNet, Whisper, and ContentVec.Read 5 Oct 2026 · github.com
Generation tasks
Supported tasks include text-to-speech, singing voice synthesis, voice conversion, accent conversion, singing voice conversion, and text-to-audio; text-to-music is listed as in development.Read 4 Oct 2026 · github.com
Installation
The README documents installation with a setup installer using Python 3.9.15 and with a Docker image.Read 5 Oct 2026 · github.com
Integrations and dependencies
The project lists WeNet, Whisper, and ContentVec among pretrained models used for content-based features, and its Docker instructions require NVIDIA drivers, NVIDIA Container Toolkit, and CUDA.Read 4 Oct 2026 · github.com
License and cost
Amphion is licensed under MIT and the README says it is free for research and commercial use.Read 4 Oct 2026 · github.com
Models
The toolkit implements diffusion, transformer, VAE, and flow-based model architectures.Read 5 Oct 2026 · github.com
Singing generation
Vevo2 supports controllable speech and singing generation, including voice conversion, singing voice conversion, singing voice editing, singing style conversion, and melody control.Read 4 Oct 2026 · github.com
Support and community
The project invites contributions and links to a Discord channel for community engagement.Read 4 Oct 2026 · github.com
Supported tasks
The README marks text-to-speech, singing voice synthesis, voice conversion, accent conversion, singing voice conversion, and text-to-audio as supported, while text-to-music is in development.Read 5 Oct 2026 · github.com
Technical limit
Text-to-music is listed as in development rather than supported.Read 5 Oct 2026 · github.com
Text to audio
Amphion supports text-to-audio generation using a latent diffusion model and describes it as the official implementation of the text-to-audio generation part of its NeurIPS 2023 paper.Read 4 Oct 2026 · github.com
Visualization
Amphion provides interactive visualizations of classic models and currently supports SingVisio for visualizing the diffusion model for singing voice conversion.Read 5 Oct 2026 · github.com
Voice and speech models
The toolkit includes architectures such as FastSpeech2, VITS, VALL-E, NaturalSpeech2, MaskGCT, and Vevo-TTS for text-to-speech, plus Vevo, FACodec, and Noro for voice conversion.Read 4 Oct 2026 · github.com
Voice cloning
YesRead 20 Sep 2026 · github.com

Plans and prices

Amphion Free MIT-licensed · free for research and commercial use Read 5 Oct 2026 · github.com

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