AASP-L11.5
A HYBRID DEEP-ONLINE LEARNING BASED METHOD FOR ACTIVE NOISE CONTROL IN WAVE DOMAIN
Donghang Wu, Xihong Wu, Tianshu Qu, Peking University, China
Session:
AASP-L11: Active noise control and echo cancellation Lecture
Track:
Audio and Acoustic Signal Processing
Location:
Room 201
Presentation Time:
Thu, 18 Apr, 17:50 - 18:10 (UTC +9)
Session Co-Chairs:
Thushara Abhayapala, Australian National University and Daniele Giacobello, Apple Inc.
Session AASP-L11
AASP-L11.1: A LIGHT-WEIGHT STATE DETECTION MODEL FOR KALMAN-FILTER-BASED ACOUSTIC FEEDBACK CANCELLATION WITH RAPID RECOVERY FROM ABRUPT PATH CHANGES
Haocheng Guo, Nanjing University, China; Xiaohuai Le, ByteDance, China; Kai Chen, Jing Lu, Nanjing University, China
AASP-L11.2: ACTIVE NOISE CONTROL OVER A LARGE REGION WITH MULTIPLE SPHERICAL MICROPHONE ARRAYS IN WAVE DOMAIN
XIAOLI TANG, Australian National University, Australia; JIHUI (AIMEE) ZHANG, University of Southampton, Australia; THUSHARA ABHAYAPALA, Australian National University, Australia
AASP-L11.3: ACTIVE NOISE CONTROL OVER 3D SPACE WITH A DYNAMIC NOISE SOURCE
Huiyuan Sun, Craig Jin, The University of Sydney, Australia; Thushara Abhayapala, Prasanga Samarasinghe, The Australian National University, Australia
AASP-L11.4: META-AF ECHO CANCELLATION FOR IMPROVED KEYWORD SPOTTING
Jonah Casebeer, Junkai Wu, Paris Smaragdis, University of Illinois at Urbana-Champaign, United States of America
AASP-L11.5: A HYBRID DEEP-ONLINE LEARNING BASED METHOD FOR ACTIVE NOISE CONTROL IN WAVE DOMAIN
Donghang Wu, Xihong Wu, Tianshu Qu, Peking University, China
AASP-L11.6: EFFICIENT HIGH-PERFORMANCE BARK-SCALE NEURAL NETWORK FOR RESIDUAL ECHO AND NOISE SUPPRESSION
Ernst Seidel, Technische Universität Braunschweig, Germany; Pejman Mowlaee, GN Audio A/S, Denmark; Tim Fingscheidt, Technische Universität Braunschweig, Germany
Contacts