Time-Frequency Networks for Audio Super-Resolution

Teck-Yian Lim, Raymond A. Yeh, Yijia Xu, Minh N. Do, Mark Hasegawa-Johnson

Abstract: Audio super-resolution (a.k.a. bandwidth extension) is the challenging task of increasing the temporal resolution of audio signals. Recent deep networks approaches achieved promising results by modeling the task as a regression problem in either time or frequency domain. In this paper, we introduced Time-Frequency Network (TFNet), a deep network that utilizes supervision in both the time and frequency domain. We proposed a novel model architecture which allows the two domains to be jointly optimized. Results demonstrate that our method outperforms the state-of-the-art both quantitatively and qualitatively.