Speech-to-Singing Conversion based on Boundary Equilibrium GAN

Da-Yi Wu; Yi-Hsuan Yang

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arXiv · 2005.13835

Speech-to-Singing Conversion based on Boundary Equilibrium GAN

Da-Yi Wu·Yi-Hsuan Yang

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Abstract

This paper investigates the use of generative adversarial network (GAN)-based models for converting the spectrogram of a speech signal into that of a singing one, without reference to the phoneme sequence underlying the speech. This is achieved by viewing speech-to-singing conversion as a style transfer problem. Specifically, given a speech input, and optionally the F0 contour of the target singing, the proposed model generates as the output a singing signal with a progressive-growing encoder/decoder architecture and boundary equilibrium GAN loss functions. Our quantitative and qualitative analysis show that the proposed model generates singing voices with much higher naturalness than an existing non adversarially-trained baseline. For reproducibility, the code will be publicly available at a GitHub repository upon paper publication.

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Da-Yi Wu, Yi-Hsuan Yang. 2020-08-05. Speech-to-Singing Conversion based on Boundary Equilibrium GAN. https://arxiv.org/abs/2005.13835

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