SingIt! Singer Voice Transformation
Audio and Speech Processing
2024-05-09 v1 Sound
Abstract
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.
Keywords
Cite
@article{arxiv.2405.04627,
title = {SingIt! Singer Voice Transformation},
author = {Amit Eliav and Aaron Taub and Renana Opochinsky and Sharon Gannot},
journal= {arXiv preprint arXiv:2405.04627},
year = {2024}
}