Technical Program

AASP-L3: Multichannel Source Separation

Session Type: Lecture
Time: Wednesday, May 29, 10:30 - 12:30
Location: Room 110
Session Chair: Shoji Makino, University of Tsukuba
 
AASP-L3.1: INFORMED SOURCE SEPARATION FROM COMPRESSED MIXTURES USING SPATIAL WIENER FILTER AND QUANTIZATION NOISE ESTIMATION
         Shuhua Zhang; Grenoble-INP
         Laurent Girin; Grenoble-INP
         Antoine Liutkus; Institut Mines-Telecom, CNRS LTCI
 
AASP-L3.2: LOW BITRATE INFORMED SOURCE SEPARATION OF REALISTIC MIXTURES
         Antoine Liutkus; Télécom ParisTech, Institut Mines-Telecom, CNRS LTCI
         Roland Badeau; Télécom ParisTech, Institut Mines-Telecom, CNRS LTCI
         Gaël Richard; Télécom ParisTech, Institut Mines-Telecom, CNRS LTCI
 
AASP-L3.3: SOUND SOURCE SEPARATION BASED ON NON-NEGATIVE TENSOR FACTORIZATION INCORPORATING SPATIAL CUE AS PRIOR KNOWLEDGE
         Yuki Mitsufuji; Sony Corporation
         Axel Roebel; IRCAM-CNRS-UPMC UMR 9912
 
AASP-L3.4: VARIATIONAL EM FOR BINAURAL SOUND-SOURCE SEPARATION AND LOCALIZATION
         Antoine Deleforge; INRIA Grenoble Rhône-Alpes
         Florence Forbes; INRIA Grenoble Rhône-Alpes
         Radu Horaud; INRIA Grenoble Rhône-Alpes
 
AASP-L3.5: UNDERDETERMINED INSTANTANEOUS BLIND SOURCE SEPARATION OF SPARSE SIGNALS WITH TEMPORAL STRUCTURE USING THE STATE-SPACE MODEL
         Benxu Liu; Nanyang Technological University
         Vaninirappuputhenpurayil Gopalan Reju; Nanyang Technological University
         Andy W.H. Khong; Nanyang Technological University
 
AASP-L3.6: UNSUPERVISED SPATIAL DICTIONARY LEARNING FOR SPARSE UNDERDETERMINED MULTICHANNEL SOURCE SEPARATION
         Francesco Nesta; Fondazione Bruno Kessler
         Mahmoud Fakhry; Fondazione Bruno Kessler