ASMSP-SS3.1
Learning Source Model for Independent Vector Extraction by Score Matching
Zbyněk Koldovský, Matěj Navrátil, Jiří Málek, Technical University of Liberec, Czech Republic
Session:
Advanced Signal Processing and Machine Learning for Acoustic Scene Analysis and Signal Enhancement Lecture
Track:
20: Advanced Signal Processing and Machine Learning for Acoustic Scene Analysis and Signal Enhancement
Location:
Concert Hall
Session Time:
Fri, 4 Sep, 10:30 - 12:30
Presentation Time:
Fri, 4 Sep, 10:30 - 10:50
Session Co-Chairs:
Shoji Makino, Waseda University and Nobutaka Ono, Tokyo Metropolitan University
Presentation
Discussion
Session ASMSP-SS3
ASMSP-SS3.1: Learning Source Model for Independent Vector Extraction by Score Matching
Zbyněk Koldovský, Matěj Navrátil, Jiří Málek, Technical University of Liberec, Czech Republic
ASMSP-SS3.2: Introduction of Time-Frequency Masking to Switching Beamformers for Distortionless Blind Source Separation in Underdetermined Situations
Atsuhisa Nakane, Kouei Yamaoka, Norihiro Takamune, Hiroshi Saruwatari, The University of Tokyo, Japan; Daichi Kitamura, National Institute of Technology, Kagawa College, Japan; Rintaro Ikeshita, Tomohiro Nakatani, NTT, Inc., Japan
ASMSP-SS3.3: Context-Aware Sensor Fusion: Robust 6DoF Audio Tracking via Sound Scene Analysis
Jun-Wei Yeow, Ee-Leng Tan, Santi Peksi, Woon-Seng Gan, Nanyang Technological University, Singapore
ASMSP-SS3.4: Multi-Channel Replay Speech Detection using Acoustic Maps
Michael Neri, Tuomas Virtanen, Tampere University, Finland
ASMSP-SS3.5: Subspace-Constrained Iterative Source Steering for Multichannel Source Separation
Yutsuki Takeuchi, Taishi Nakashima, Nobutaka Ono, Tokyo Metropolitan University, Japan
ASMSP-SS3.6: ON THE USEFULNESS OF DIFFUSION-BASED ROOM IMPULSE RESPONSE INTERPOLATION TO MICROPHONE ARRAY PROCESSING
Sagi Della Torre, Bar-Ilan University, Israel; Mirco Pezzoli, Fabio Antonacci, Politecnico di Milano, Israel; Sharon Gannot, Bar-Ilan University, Israel
Resources
No resources available.