Technical Program

Paper Detail

Paper IDAUD-L2.6
Paper Title UNSUPERVISED TRAINING FOR DEEP SPEECH SOURCE SEPARATION WITH KULLBACK-LEIBLER DIVERGENCE BASED PROBABILISTIC LOSS FUNCTION
Authors Masahito Togami, LINE Corporation, Japan; Yoshiki Masuyama, Waseda University, Japan; Tatsuya Komatsu, LINE Corporation, Japan; Yu Nakagome, Waseda University, Japan
SessionAUD-L2: Deep Learning for Source Separation
LocationOn-Demand
Session Time:Tuesday, 05 May, 16:30 - 18:30
Presentation Time:Tuesday, 05 May, 18:10 - 18:30
Presentation Lecture
Topic Audio and Acoustic Signal Processing: [AUD-SEP] Audio and Speech Source Separation
IEEE Xplore Open Preview  Click here to view in IEEE Xplore
Virtual Presentation  Click here to watch in the Virtual Conference