MLSP-46.3
REMIX-CYCLE-CONSISTENT LEARNING ON ADVERSARIALLY LEARNED SEPARATOR FOR ACCURATE AND STABLE UNSUPERVISED SPEECH SEPARATION
Kohei Saijo, Tetsuji Ogawa, Waseda University, Japan
Session:
Source Separation and ICA
Track:
Machine Learning for Signal Processing
Location:
Gather Area H
Presentation Time:
Thu, 12 May, 22:00 - 22:45 China Time (UTC +8)
Thu, 12 May, 14:00 - 14:45 UTC
Thu, 12 May, 14:00 - 14:45 UTC
Session Chair:
Nicolas Gillis, University of Mons
Session MLSP-46
MLSP-46.1: DMANET: DEEP LEARNING-BASED DIFFERENTIAL MICROPHONE ARRAYS FOR MULTI-CHANNEL SPEECH SEPARATION
Xiaokang Yang, Jianguo Wei, Tianjin University, China
MLSP-46.2: AMICABLE EXAMPLES FOR INFORMED SOURCE SEPARATION
Naoya Takahashi, Yuki Mitsufuji, Sony Group Corporation, Japan
MLSP-46.3: REMIX-CYCLE-CONSISTENT LEARNING ON ADVERSARIALLY LEARNED SEPARATOR FOR ACCURATE AND STABLE UNSUPERVISED SPEECH SEPARATION
Kohei Saijo, Tetsuji Ogawa, Waseda University, Japan
MLSP-46.4: AN INFORMATION MAXIMIZATION BASED BLIND SOURCE SEPARATION APPROACH FOR DEPENDENT AND INDEPENDENT SOURCES
Alper Erdogan, Koc University, Turkey
MLSP-46.5: BLIND SEPARATION OF LINEAR-QUADRATIC MIXTURES OF MUTUALLY INDEPENDENT AND AUTOCORRELATED SOURCES
Shahram Hosseini, Yannick Deville, Toulouse university, France
MLSP-46.6: LARGE-SCALE INDEPENDENT COMPONENT ANALYSIS BY SPEEDING UP LIE GROUP TECHNIQUES
Matthias Hermann, Georg Umlauf, Matthias O. Franz, HTWG Konstanz, Germany