Title
INTERSPEECH 2021 Deep Noise Suppression Challenge.
Abstract
The Deep Noise Suppression (DNS) challenge is designed to foster innovation in the area of noise suppression to achieve superior perceptual speech quality. We recently organized a DNS challenge special session at INTERSPEECH and ICASSP 2020. We open-sourced training and test datasets for the wideband scenario. We also open-sourced a subjective evaluation framework based on ITU-T standard P.808, which was also used to evaluate participants of the challenge. Many researchers from academia and industry made significant contributions to push the field forward, yet even the best noise suppressor was far from achieving superior speech quality in challenging scenarios. In this version of the challenge organized at INTERSPEECH 2021, we are expanding both our training and test datasets to accommodate full band scenarios. The two tracks in this challenge will focus on real-time denoising for (i) wide band, and(ii) full band scenarios. We are also making available a reliable non-intrusive objective speech quality metric called DNSMOS for the participants to use during their development phase.
Year
DOI
Venue
2021
10.21437/Interspeech.2021-1609
Interspeech
DocType
Citations 
PageRank 
Conference
13
0.64
References 
Authors
0
10
Name
Order
Citations
PageRank
Chandan K. Reddy180373.50
Harishchandra Dubey2141.70
Kazuhito Koishida3152.04
Arun Nair4130.98
Vishak Gopal5142.04
Ross Cutler615718.29
Sebastian Braun7365.61
Hannes Gamper86110.76
Robert Aichner920816.18
Sriram Srinivasan1037927.92