Amphion Singing Voice Conversion Pretrained Models

Quick Start

We provide a DiffWaveNetSVC pretrained checkpoint for you to play. Specially, it is trained under the real-world vocalist data (total duration: 6.16 hours), including the following 15 professional singers:

To make these singers sing the songs you want to listen to, just run the following commands:

Step1: Download the checkpoint

git lfs install
git clone https://huggingface.co/amphion/singing_voice_conversion

Step2: Clone the Amphion's Source Code of GitHub

git clone https://github.com/open-mmlab/Amphion.git

Step3: Specify the checkpoint's path

Use the soft link to specify the downloaded checkpoint in first step:

cd Amphion
mkdir ckpts/svc
ln -s ../singing_voice_conversion/vocalist_l1_contentvec+whisper ckpts/svc/vocalist_l1_contentvec+whisper

Step4: Conversion

You can follow this recipe to conduct the conversion. For example, if you want to make Taylor Swift sing the songs in the [Your Audios Folder], just run:

sh egs/svc/MultipleContentsSVC/run.sh --stage 3 --gpu "0" \
    --config "ckpts/svc/vocalist_l1_contentvec+whisper/args.json" \
    --infer_expt_dir "ckpts/svc/vocalist_l1_contentvec+whisper" \
    --infer_output_dir "ckpts/svc/vocalist_l1_contentvec+whisper/result" \
    --infer_source_audio_dir [Your Audios Folder] \
    --infer_target_speaker "vocalist_l1_TaylorSwift" \
    --infer_key_shift "autoshift"

Note: The supported infer_target_speaker values can be seen here.

Citaions

@article{zhang2023leveraging,
  title={Leveraging Content-based Features from Multiple Acoustic Models for Singing Voice Conversion},
  author={Zhang, Xueyao and Gu, Yicheng and Chen, Haopeng and Fang, Zihao and Zou, Lexiao and Xue, Liumeng and Wu, Zhizheng},
  journal={Machine Learning for Audio Worshop, NeurIPS 2023},
  year={2023}
}