MLSP-20.4
DEEP-MLE: FUSION BETWEEN A NEURAL NETWORK AND MLE FOR A SINGLE SNAPSHOT DOA ESTIMATION
Marcio L. Lima de Oliveira, University of Twente, Netherlands; Marco Bekooij, NXP Semiconductors, Netherlands
Session:
Data Science Initiative I
Track:
Machine Learning for Signal Processing
Location:
Gather Area F
Presentation Time:
Mon, 9 May, 23:00 - 23:45 China Time (UTC +8)
Mon, 9 May, 15:00 - 15:45 UTC
Mon, 9 May, 15:00 - 15:45 UTC
Session Chair:
Sharon Gannot, Bar-Ilan University
Session MLSP-20
MLSP-20.1: EXPLORING HETEROGENEOUS CHARACTERISTICS OF LAYERS IN ASR MODELS FOR MORE EFFICIENT TRAINING
Lillian Zhou, Dhruv Guliani, Andreas Kabel, Giovanni Motta, Françoise Beaufays, Google LLC, United States of America
MLSP-20.2: PROBABILISTIC FINE-GRAINED URBAN FLOW INFERENCE WITH NORMALIZING FLOWS
Ting Zhong, Haoyang Yu, Rongfan Li, Xovee Xu, Xucheng Luo, Fan Zhou, University of Electronic Science and Technology of China, China
MLSP-20.3: ATTENTION-BASED DUAL-STREAM VISION TRANSFORMER FOR RADAR GAIT RECOGNITION
Shiliang Chen, Wentao He, Jianfeng Ren, University of Nottingham Ningbo China, China; Xudong Jiang, Nanyang Technological University, Singapore
MLSP-20.4: DEEP-MLE: FUSION BETWEEN A NEURAL NETWORK AND MLE FOR A SINGLE SNAPSHOT DOA ESTIMATION
Marcio L. Lima de Oliveira, University of Twente, Netherlands; Marco Bekooij, NXP Semiconductors, Netherlands
MLSP-20.5: SELECTIVE MUTUAL LEARNING: AN EFFICIENT APPROACH FOR SINGLE CHANNEL SPEECH SEPARATION
MinhTan Ha, Duc-Quang Vu, Chung-Ting Lee, Yung-Hui Li, Jia-Ching Wang, National Central University, Taiwan
MLSP-20.6: DETECTION OF COVID-19 FROM JOINT TIME AND FREQUENCY ANALYSIS OF SPEECH, BREATHING AND COUGH AUDIO
John Harvill, Moitreya Chatterjee, Mark Hasegawa-Johnson, Narendra Ahuja, University of Illinois at Urbana-Champaign, United States of America; Yash Wani, Mustafa Alam, David Beiser, University of Chicago, United States of America; David Chestek, University of Illinois at Chicago, United States of America