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Time-Frequency Networks for Audio Super-Resolution

Citation Author(s):
Yijia Xu, Minh N. Do, Mark Hasegawa-Johnson
Submitted by:
Teck Yian Lim
Last updated:
17 April 2018 - 12:54am
Document Type:
Poster
Document Year:
2018
Event:
Presenters Name:
Teck Yian Lim
Paper Code:
3828

Abstract 

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.

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