MLSP-6.3
SELF-SUPERVISED LEARNING METHOD USING MULTIPLE SAMPLING STRATEGIES FOR GENERAL-PURPOSE AUDIO REPRESENTATION
Ibuki Kuroyanagi, Nagoya University, Japan; Tatsuya Komatsu, LINE Corporation, Japan
Session:
Self-supervised Learning for Speech and Audio Processing II
Track:
Machine Learning for Signal Processing
Location:
Gather Area H
Presentation Time:
Sun, 8 May, 21:00 - 21:45 China Time (UTC +8)
Sun, 8 May, 13:00 - 13:45 UTC
Sun, 8 May, 13:00 - 13:45 UTC
Session Chair:
Hung-yi Lee, National Taiwan University
Session MLSP-6
MLSP-6.1: SELF-SUPERVISED ACOUSTIC ANOMALY DETECTION VIA CONTRASTIVE LEARNING
Hadi Hojjati, Narges Armanfard, McGill University, Canada
MLSP-6.2: DON'T SPEAK TOO FAST: THE IMPACT OF DATA BIAS ON SELF-SUPERVISED SPEECH MODELS
Yen Meng, Yi-Hui Chou, Andy T. Liu, Hung-yi Lee, National Taiwan University, Taiwan
MLSP-6.3: SELF-SUPERVISED LEARNING METHOD USING MULTIPLE SAMPLING STRATEGIES FOR GENERAL-PURPOSE AUDIO REPRESENTATION
Ibuki Kuroyanagi, Nagoya University, Japan; Tatsuya Komatsu, LINE Corporation, Japan
MLSP-6.4: Self supervised representation learning with deep clustering for acoustic unit discovery from raw speech
Varun Krishna, Sriram Ganapathy, LEAP lab, Indian Institute of Science, Bangalore, India., India
MLSP-6.5: T-NGA: TEMPORAL NETWORK GRAFTING ALGORITHM FOR LEARNING TO PROCESS SPIKING AUDIO SENSOR EVENTS
Shu Wang, Yuhuang Hu, Shih-Chii Liu, Institute of Neuroinformatics, University of Zürich and ETH Zürich, Switzerland
MLSP-6.6: CONTRASTIVE KNOWLEDGE GRAPH ATTENTION NETWORK FOR REQUEST-BASED RECIPE RECOMMENDATION
Xiyao Ma, Zheng Gao, Qian Hu, Mohamed AbdelHady, Amazon Alexa AI, United States of America