Spectrum Enhancement of Singing Voice Using Deep Learning
Ryuka Nanzaka, T. Kitamura, Tetsuya Takiguchi, Yuji Adachi, Kiyoto Tai · 2018
In this paper, we propose a novel singing-voice enhancement system that makes the singing voice of amateurs similar to that of professional opera singers, where the singing voice of amateurs is emphasized by using a singing voice of a professional opera singer on a frequency band that represents the remarkable characteristic of the professional singer. Moreover, our proposed singing-voice enhancement based on highway networks is able to convert any song (that a professional opera singer does not sing). As a result of our experiments, the singing voice of the amateur singer at the middle-high frequency range which contains a lot of frequency components that affect glossiness was emphasized while maintaining speaker characteristics.