AASP-P1: Audio events detection and classification; Music Information Retrieval 1
Tue, 16 Apr, 13:10 - 15:10 (UTC +9)
Location: Poster Zone 1A
Session Type: Poster
Session Chair: Dasaem Jeong, Sogang University
Track: Audio and Acoustic Signal Processing
Click the to view the manuscript on IEEE Xplore Open Preview
 

AASP-P1.1: SEMI-SUPERVISED SOUND EVENT DETECTION WITH LOCAL AND GLOBAL CONSISTENCY REGULARIZATION

Yiming Li, Xiangdong Wang, Hong Liu, Institute of Computing Technology, Chinese Academy of Sciences, China; Rui Tao, Long Yan, Toshiba(china), China; Kazushige Ouchi, Toshiba (China) Co., Ltd, Japan
 

AASP-P1.2: ”IT IS OKAY TO BE UNCOMMON”: QUANTIZING SOUND EVENT DETECTION NETWORKS ON HARDWARE ACCELERATORS WITH UNCOMMON SUB-BYTE SUPPORT

Yushu Wu, Northeastern University, United States of America; Xiao Quan, Russell Izadi, Chuan-Che Huang, Bose Corporation, United States of America
 

AASP-P1.3: FINE-TUNE THE PRETRAINED ATST MODEL FOR SOUND EVENT DETECTION

Nian Shao, Zhejiang University; Westlake University, China; Xian Li, Xiaofei Li, Westlake University; Westlake Institute for Advanced Study, China
 

AASP-P1.4: A UNIFIED LOSS FUNCTION TO TACKLE INTER-CLASS AND INTRA-CLASS DATA IMBALANCE IN SOUND EVENT DETECTION

Yuliang Zhang, Roberto Togneri, David Huang, The University of Western Australia, Australia
 

AASP-P1.5: ACTIVE LEARNING FOR SOUND EVENT CLASSIFICATION USING BAYESIAN NEURAL NETWORKS WITH GAUSSIAN VARIATIONAL POSTERIOR

Stepan Shishkin, Danilo Hollosi, Fraunhofer Institute for Digital Media Technology IDMT, Germany; Stefan Goetze, The University of Sheffield, United Kingdom of Great Britain and Northern Ireland; Simon Doclo, Carl von Ossietzky Universität Oldenburg, Germany
 

AASP-P1.6: SSL-NET: A SYNERGISTIC SPECTRAL AND LEARNING-BASED NETWORK FOR EFFICIENT BIRD SOUND CLASSIFICATION

Yiyuan Yang, Kaichen Zhou, Niki Trigoni, Andrew Markham, University of Oxford, United Kingdom of Great Britain and Northern Ireland
 

AASP-P1.7: CLASS-INCREMENTAL LEARNING FOR MULTI-LABEL AUDIO CLASSIFICATION

Manjunath Mulimani, Annamaria Mesaros, Tampere University, Finland
 

AASP-P1.8: AN EXPLAINABLE PROXY MODEL FOR MULTILABEL AUDIO SEGMENTATION

Théo Mariotte, Le Mans Université, France; Antonio Almudévar, University of Zaragoza, Spain; Marie Tahon, Le Mans Université, France; Alfonso Ortega, University of Zaragoza, Spain
 

AASP-P1.9: A FOUNDATION MODEL FOR MUSIC INFORMATICS

Minz Won, Suno, United States of America; Yun-Ning Hung, Duc Le, ByteDance, United States of America
 

AASP-P1.10: PIANO TRANSCRIPTION WITH HARMONIC ATTENTION

Ruimin Wu, Xianke Wang, Yuqing Li, Wei Xu, Wenqing Cheng, School of Electronic Information and Communications, Hubei Provincial Key Laboratory of Smart Internet Technology, Huazhong University of Science and Technology, China
 

AASP-P1.11: TIMBRE-TRAP: A LOW-RESOURCE FRAMEWORK FOR INSTRUMENT-AGNOSTIC MUSIC TRANSCRIPTION

Frank Cwitkowitz, University of Rochester, United States of America; Kin Wai Cheuk, Woosung Choi, Marco Martínez-Ramírez, Keisuke Toyama, Wei-Hsiang Liao, Yuki Mitsufuji, Sony, Japan
 

AASP-P1.12: TEMPO ESTIMATION AS FULLY SELF-SUPERVISED BINARY CLASSIFICATION

Florian Henkel, Jaehun Kim, Matthew McCallum, Samuel Sandberg, Matthew Davies, SiriusXM-Pandora, United States of America