SingIt! Singer Voice Transformation
<|reference_start|>SingIt! Singer Voice Transformation: In this paper, we propose a model which can generate a singing voice from normal speech utterance by harnessing zero-shot, many-to-many style transfer learning. Our goal is to give anyone the opportunity to sing any song in a timely manner. We present a system comprising several available blocks, as well as a modified auto-encoder, and show how this highly-complex challenge can be achieved by tailoring rather simple solutions together. We demonstrate the applicability of the proposed system using a group of 25 non-expert listeners. Samples of the data generated from our model are provided.<|reference_end|>
@article{eliav2024singit!,
    title={SingIt! Singer Voice Transformation},
    author={Amit Eliav, Aaron Taub, Renana Opochinsky, Sharon Gannot},
    journal={arXiv preprint arXiv:2405.04627},
    year={2024},
    archivePrefix={arXiv},
    eprint={2405.04627},
    primaryClass={eess.AS cs.SD}
}