activity
20192022
most citedInteractive Speech and Noise Modeling for Speech Enhancement

4 citations · 8 across the 5 of their papers we have counts for

collaborators

11 papers

eess.AS20221 cited

SCA: Streaming Cross-attention Alignment for Echo Cancellation

Yang Liu, Yangyang Shi, Yun Li +3

End-to-End deep learning has shown promising results for speech enhancement tasks, such as noise suppression, dereverberation, and speech separation. However, most state-of-the-art…

eess.AS20223 cited

ICASSP 2022 Deep Noise Suppression Challenge

Harishchandra Dubey, Vishak Gopal, Ross Cutler +8

The Deep Noise Suppression (DNS) challenge is designed to foster innovation in the area of noise suppression to achieve superior perceptual speech quality. This is the 4th DNS chal…

cs.SD2021

Interspeech 2021 Deep Noise Suppression Challenge

Chandan K A Reddy, Harishchandra Dubey, Kazuhito Koishida +7

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…

eess.AS20204 cited

Interactive Speech and Noise Modeling for Speech Enhancement

Chengyu Zheng, Xiulian Peng, Yuan Zhang +2

Speech enhancement is challenging because of the diversity of background noise types. Most of the existing methods are focused on modelling the speech rather than the noise. In thi…

cs.AI2020

Resonance: Replacing Software Constants with Context-Aware Models in Real-time Communication

Jayant Gupchup, Ashkan Aazami, Yaran Fan +23

Large software systems tune hundreds of 'constants' to optimize their runtime performance. These values are commonly derived through intuition, lab tests, or A/B tests. A 'one-size…

eess.AS2020

ICASSP 2021 Acoustic Echo Cancellation Challenge: Datasets, Testing Framework, and Results

Kusha Sridhar, Ross Cutler, Ando Saabas +6

The ICASSP 2021 Acoustic Echo Cancellation Challenge is intended to stimulate research in the area of acoustic echo cancellation (AEC), which is an important part of speech enhance…