AUD-25.6
END-TO-END DEEP LEARNING-BASED ADAPTATION CONTROL FOR FREQUENCY-DOMAIN ADAPTIVE SYSTEM IDENTIFICATION
Thomas Haubner, Andreas Brendel, Walter Kellermann, Friedrich-Alexander-University Erlangen-Nuremberg, Germany
Session:
Active Noise Control, Echo Reduction, and Feedback Reduction II
Track:
Audio and Acoustic Signal Processing
Location:
Gather Area K
Presentation Time:
Thu, 12 May, 20:00 - 20:45 China Time (UTC +8)
Thu, 12 May, 12:00 - 12:45 UTC
Thu, 12 May, 12:00 - 12:45 UTC
Session Chair:
Ina Kodrasi, IDIAP
Session AUD-25
AUD-25.1: DEEP ADAPTATION CONTROL FOR ACOUSTIC ECHO CANCELLATION
Amir Ivry, Israel Cohen, Baruch Berdugo, Technion - Israel Institute of Technology, Israel
AUD-25.2: OFF-THE-SHELF DEEP INTEGRATION FOR RESIDUAL-ECHO SUPPRESSION
Amir Ivry, Israel Cohen, Baruch Berdugo, Technion - Israel Institute of Technology, Israel
AUD-25.3: A COMPLEX SPECTRAL MAPPING WITH INPLACE CONVOLUTION RECURRENT NEURAL NETWORKS FOR ACOUSTIC ECHO CANCELLATION
Chenggang Zhang, Jinjiang Liu, Xueliang Zhang, Inner Mongolia University, China
AUD-25.4: DEEP ADAPTIVE AEC: HYBRID OF DEEP LEARNING AND ADAPTIVE ACOUSTIC ECHO CANCELLATION
Hao Zhang, The Ohio State University, United States of America; Srivatsan Kandadai, Harsha Rao, Tarun Pruthi, Trausti Kristjansson, Amazon Inc, United States of America; Minje Kim, Indiana University, United States of America
AUD-25.5: COMPUTATIONALLY EFFICIENT FIXED-FILTER ANC FOR SPEECH BASED ON LONG-TERM PREDICTION FOR HEADPHONE APPLICATIONS
Yurii Iotov, Mads Græsbøll Christensen, Aalborg University, Denmark; Sidsel Marie Nørholm, Valiantsin Belyi, Mads Dyrholm, GN Audio A/S, Denmark
AUD-25.6: END-TO-END DEEP LEARNING-BASED ADAPTATION CONTROL FOR FREQUENCY-DOMAIN ADAPTIVE SYSTEM IDENTIFICATION
Thomas Haubner, Andreas Brendel, Walter Kellermann, Friedrich-Alexander-University Erlangen-Nuremberg, Germany