SoulX-Singer: Towards High-Quality Zero-Shot Singing Voice Synthesis
While recent years have witnessed rapid progress in speech synthesis, open-source singing voice synthesis (SVS) systems still face significant barriers to industrial deployment, particularly in terms of robustness and zero-shot generalization. In this report, we introduce SoulX-Singer, a high-quality open-source SVS system designed with practical deployment considerations in mind. SoulX-Singer supports controllable singing generation conditioned on either symbolic musical scores (MIDI) or melodic representations, enabling flexible and expressive control in real-world production workflows. Trained on more than 42,000 hours of vocal data, the system supports Mandarin Chinese, English, and Cantonese and consistently achieves state-of-the-art synthesis quality across languages under diverse musical conditions. Furthermore, to enable reliable evaluation of zero-shot SVS performance in practical scenarios, we construct SoulX-Singer-Eval, a dedicated benchmark with strict training-test disentanglement, facilitating systematic assessment in zero-shot settings.
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Jiale Qian
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Hao Meng
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Tian Zheng
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Pengcheng Zhu
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Haopeng Lin
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Yuhang Dai
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Hanke Xie
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Wenxiao Cao
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Ruixuan Shang
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Jun Wu
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Hongmei Liu
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Hanlin Wen
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Jian Zhao
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Zhonglin Jiang
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Yong Chen
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Shunshun Yin
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Ming Tao
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Jianguo Wei
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Lei Xie
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Xinsheng Wang
SoulX-Singer: Towards High-Quality Zero-Shot Singing Voice Synthesis
While recent years have witnessed rapid progress in speech synthesis, open-source singing voice synthesis (SVS) systems still face significant barriers to industrial deployment, particularly in terms of robustness and zero-shot generalization. In this report, we introduce SoulX-Singer, a high-quality open-source SVS system designed with practical deployment considerations in mind. SoulX-Singer supports controllable singing generation conditioned on either symbolic musical scores (MIDI) or melodic representations, enabling flexible and expressive control in real-world production workflows. Trained on more than 42,000 hours of vocal data, the system supports Mandarin Chinese, English, and Cantonese and consistently achieves state-of-the-art synthesis quality across languages under diverse musical conditions. Furthermore, to enable reliable evaluation of zero-shot SVS performance in practical scenarios, we construct SoulX-Singer-Eval, a dedicated benchmark with strict training-test disentanglement, facilitating systematic assessment in zero-shot settings.
A high-quality open-source singing voice synthesis system is presented with support for multiple languages and controllable generation, along with a dedicated benchmark for evaluating zero-shot performance.
singing voice synthesis symbolic musical scores melodic representations zero-shot generalization speech synthesis Mandarin Chinese English Cantonese