Learning Bandwidth Expansion Using Perceptually-Motivated Loss
Published in ICASSP, 2019
Recommended citation: Berthy Feng, Zeyu Jin, Jiaqi Su, and Adam Finkelstein. "Learning Bandwidth Expansion Using Perceptually-Motivated Loss." ICASSP, May 2019. https://pixl.cs.princeton.edu/pubs/Feng_2019_LBE/Feng_2019_bwe.pdf
We introduce a perceptually motivated approach to bandwidth expansion for speech. Our method pairs a new three-way split variant of the FFTNet neural vocoder structure with a perceptual loss function, combining objectives from both the time and frequency domains. Mean opinion score tests show that it outperforms baseline methods from both domains, even for extreme bandwidth expansion.