Official inference code for
SoulX-Singer: Towards High-Quality Zero-Shot Singing Voice Synthesis
SoulX-Singer is a high-fidelity, zero-shot singing voice synthesis model that enables users to generate realistic singing voices for unseen singers.
It supports melody-conditioned (F0 contour) and score-conditioned (MIDI notes) control for precise pitch, rhythm, and expression.
- π€ Zero-Shot Singing β Generate high-fidelity voices for unseen singers, no fine-tuning needed.
- π΅ Flexible Control Modes β Melody (F0) and Score (MIDI) conditioning.
- π Large-Scale Dataset β 42,000+ hours of aligned vocals, lyrics, notes across Mandarin, English, Cantonese.
- π§βπ€ Timbre Cloning β Preserve singer identity across languages, styles, and edited lyrics.
- βοΈ Singing Voice Editing β Modify lyrics while keeping natural prosody.
- π Cross-Lingual Synthesis β High-fidelity synthesis by disentangling timbre from content.
-Soul-Singer.mp4
-Soux-Singer.mp4
- [2026-02-12] SoulX-Singer Eval Dataset is now available on Hugging Face Datasets.
- [2026-02-09] SoulX-Singer Online Demo is live on Hugging Face Spaces β try singing voice synthesis in your browser.
- [2026-02-08] MIDI Editor is available on Hugging Face Spaces.
- [2026-02-06] SoulX-Singer inference code and models released.
git clone https://github.com/Soul-AILab/SoulX-Singer.git
cd SoulX-Singer1. Install Conda (if not already installed): https://docs.conda.io/en/latest/miniconda.html
2. Create and activate a Conda environment:
conda create -n soulxsinger -y python=3.10
conda activate soulxsinger
3. Install dependencies:
pip install -r requirements.txt
pip install -r requirements.txt -i https://mirrors.aliyun.com/pypi/simple/ --trusted-host=mirrors.aliyun.com
Install Hugging Face Hub if needed:
pip install -U huggingface_hub
Download the SVS model and preprocessing models:
pip install -U huggingface_hub
# Download the SoulX-Singer SVS model
hf download Soul-AILab/SoulX-Singer --local-dir pretrained_models/SoulX-Singer
# Download models required for preprocessing
hf download Soul-AILab/SoulX-Singer-Preprocess --local-dir pretrained_models/SoulX-Singer-PreprocessRun the inference demo:
bash example/infer.shThis script relies on metadata generated from the preprocessing pipeline, including vocal separation and transcription. Users should follow the steps in preprocess to prepare the necessary metadata before running the demo with their own data.
How to use the Midi-Editor:
You can launch the interactive interface with:
python webui.py
- π₯οΈ Web-based UI for easy and interactive inference
- π Online MIDI Editor deployment on Hugging Face Spaces
- π Online demo deployment on Hugging Face Spaces
- π Release the SoulX-Singer-Eval benchmark
- πΉ Inference support for user-friendly MIDI-based input
- π Comprehensive tutorials and usage documentation
- π΅ Support for wav-to-wav singing voice conversion (without transcription)
Special thanks to the following open-source projects:
- F5-TTS
- Amphion
- Music Source Separation Training
- Lead Vocal Separation
- Vocal Dereverberation
- RMVPE Paraformer
- Parakeet-tdt-0.6b-v2
- ROSVOT
We use the Apache 2.0 license. Researchers and developers are free to use the codes and model weights of our SoulX-Singer. Check the license at LICENSE for more details.
SoulX-Singer is intended for academic research, educational purposes, and legitimate applications such as personalized singing synthesis and assistive technologies.
Please note:
- π€ Respect intellectual property, privacy, and personal consent when generating singing content.
- π« Do not use the model to impersonate individuals without authorization or to create deceptive audio.
β οΈ The developers assume no liability for any misuse of this model.
We advocate for the responsible development and use of AI and encourage the community to uphold safety and ethical principles. For ethics or misuse concerns, please contact us.
If you use SoulX-Singer in your research, please cite:
@misc{soulxsinger,
title={SoulX-Singer: Towards High-Quality Zero-Shot Singing Voice Synthesis},
author={Jiale Qian and Hao Meng and Tian Zheng and Pengcheng Zhu and Haopeng Lin and Yuhang Dai and Hanke Xie and Wenxiao Cao and Ruixuan Shang and Jun Wu and Hongmei Liu and Hanlin Wen and Jian Zhao and Zhonglin Jiang and Yong Chen and Shunshun Yin and Ming Tao and Jianguo Wei and Lei Xie and Xinsheng Wang},
year={2026},
eprint={2602.07803},
archivePrefix={arXiv},
primaryClass={eess.AS},
url={https://arxiv.org/abs/2602.07803},
}We welcome your feedback, questions, and collaboration:
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Email: [email protected] | [email protected] | [email protected]
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