activity
20192022
most citedWeighted Speech Distortion Losses for Neural-network-based Real-time Speech Enhancement

17 citations · 20 across the 6 of their papers we have counts for

collaborators

16 papers

eess.AS2022

ICASSP 2022 Acoustic Echo Cancellation Challenge

Ross Cutler, Ando Saabas, Tanel Parnamaa +5

The ICASSP 2022 Acoustic Echo Cancellation Challenge is intended to stimulate research in acoustic echo cancellation (AEC), which is an important area of speech enhancement and sti…

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…

eess.AS2021

Performance optimizations on deep noise suppression models

Jerry Chee, Sebastian Braun, Vishak Gopal +1

We study the role of magnitude structured pruning as an architecture search to speed up the inference time of a deep noise suppression (DNS) model. While deep learning approaches h…

eess.AS2021

Low complexity online convolutional beamforming

Sebastian Braun, Ivan Tashev

Convolutional beamformers integrate the multichannel linear prediction model into beamformers, which provide good performance and optimality for joint dereverberation and noise red…

eess.AS2021

On training targets for noise-robust voice activity detection

Sebastian Braun, Ivan Tashev

The task of voice activity detection (VAD) is an often required module in various speech processing, analysis and classification tasks. While state-of-the-art neural network based…

eess.AS2021

Towards efficient models for real-time deep noise suppression

Sebastian Braun, Hannes Gamper, Chandan K. A. Reddy +1

With recent research advancements, deep learning models are becoming attractive and powerful choices for speech enhancement in real-time applications. While state-of-the-art models…