Princeton > CS Dept > PIXL > Publications Local Access 

Learning Bandwidth Expansion Using Perceptually-Motivated Loss
ICASSP, May 2019

Berthy Feng, Zeyu Jin, Jiaqi Su,
Adam Finkelstein


Abstract

We introduce a perceptually motivated approach to bandwidth expansion for speech. Our method pairs a new 3-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.

Citation (BibTeX)

Berthy Feng, Zeyu Jin, Jiaqi Su, and Adam Finkelstein. Learning Bandwidth Expansion Using Perceptually-Motivated Loss. ICASSP, May 2019.

Links
  Paper preprint
  Listen to audio clips from our experiments.