2021 IEEE International Conference on Acoustics, Speech and Signal Processing

6-11 June 2021 • Toronto, Ontario, Canada

Extracting Knowledge from Information

2021 IEEE International Conference on Acoustics, Speech and Signal Processing

6-11 June 2021 • Toronto, Ontario, Canada

Extracting Knowledge from Information

Technical Program

AUD-7: Audio and Speech Source Separation 3: Deep Learning

Session Type: Poster
Time: Wednesday, 9 June, 13:00 - 13:45
Location: Gather.Town
 
AUD-7.1: LASAFT: LATENT SOURCE ATTENTIVE FREQUENCY TRANSFORMATION FOR CONDITIONED SOURCE SEPARATION
         Woosung Choi; Korea University
         Minseok Kim; Korea University
         Jaehwa Chung; Korea National Open University
         Soonyoung Jung; Korea University
 
AUD-7.2: SURROGATE SOURCE MODEL LEARNING FOR DETERMINED SOURCE SEPARATION
         Robin Scheibler; LINE Corporation
         Masahito Togami; LINE Corporation
 
AUD-7.3: AUDITORY FILTERBANKS BENEFIT UNIVERSAL SOUND SOURCE SEPARATION
         Han Li; Northwestern Polytechnical University, Technical University of Munich
         Kean Chen; Northwestern Polytechnical University
         Bernhard U. Seeber; Technical University of Munich
 
AUD-7.4: WHAT'S ALL THE FUSS ABOUT FREE UNIVERSAL SOUND SEPARATION DATA?
         Scott Wisdom; Google
         Hakan Erdogan; Google
         Daniel P. W. Ellis; Google
         Romain Serizel; Universite de Lorraine
         Nicolas Turpault; Universite de Lorraine
         Eduardo Fonseca; Universitat Pompeu Fabra
         Justin Salamon; Adobe
         Prem Seetharaman; Descript
         John R. Hershey; Google
 
AUD-7.5: SEPNET: A DEEP SEPARATION MATRIX PREDICTION NETWORK FOR MULTICHANNEL AUDIO SOURCE SEPARATION
         Shota Inoue; University of Tsukuba
         Hirokazu Kameoka; NTT Communication Science Laboratories
         Li Li; University of Tsukuba
         Shoji Makino; University of Tsukuba
 
AUD-7.6: CDPAM: CONTRASTIVE LEARNING FOR PERCEPTUAL AUDIO SIMILARITY
         Pranay Manocha; Princeton University
         Zeyu Jin; Adobe Research
         Richard Zhang; Adobe Research
         Adam Finkelstein; Princeton University