Muskits-ESPnet: A Comprehensive Toolkit for Singing Voice Synthesis in New Paradigm
<|reference_start|>Muskits-ESPnet: A Comprehensive Toolkit for Singing Voice Synthesis in New Paradigm: This research presents Muskits-ESPnet, a versatile toolkit that introduces new paradigms to Singing Voice Synthesis (SVS) through the application of pretrained audio models in both continuous and discrete approaches. Specifically, we explore discrete representations derived from SSL models and audio codecs and offer significant advantages in versatility and intelligence, supporting multi-format inputs and adaptable data processing workflows for various SVS models. The toolkit features automatic music score error detection and correction, as well as a perception auto-evaluation module to imitate human subjective evaluating scores. Muskits-ESPnet is available at \url{https://github.com/espnet/espnet}.<|reference_end|>
@article{wu2024muskits-espnet:,
    title={Muskits-ESPnet: A Comprehensive Toolkit for Singing Voice Synthesis in
  New Paradigm},
    author={Yuning Wu and Jiatong Shi and Yifeng Yu and Yuxun Tang and Tao Qian
  and Yueqian Lin and Jionghao Han and Xinyi Bai and Shinji Watanabe and Qin
  Jin},
    journal={arXiv preprint arXiv:2409.07226},
    year={2024},
    archivePrefix={arXiv},
    eprint={2409.07226},
    primaryClass={cs.SD eess.AS}
}