2020 28Th European Signal Processing Conference
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2020 28th European Signal Processing Conference (EUSIPCO 2020) Amsterdam, Netherlands 18 -21 January 2021 Pages 1-619 IEEE Catalog Number: CFP2040S-POD ISBN: 978-1-7281-5001-7 1/4 Copyright © 2021, European Association for Signal Processing (EURASIP) All Rights Reserved *** This is a print representation of what appears in the IEEE Digital Library. Some format issues inherent in the e-media version may also appear in this print version. IEEE Catalog Number: CFP2040S-POD ISBN (Print-On-Demand): 978-1-7281-5001-7 ISBN (Online): 978-9-0827-9705-3 ISSN: 2219-5491 Additional Copies of This Publication Are Available From: Curran Associates, Inc 57 Morehouse Lane Red Hook, NY 12571 USA Phone: (845) 758-0400 Fax: (845) 758-2633 E-mail: [email protected] Web: www.proceedings.com TABLE OF CONTENTS ASMSP-1: ASMSP-1: DETECTION AND CLASSIFICATION OF ACOUSTIC SCENES AND EVENTS ASMSP-1.1: HODGE AND PODGE: HYBRID SUPERVISED SOUND EVENT DETECTION ............................................ 1 WITH MULTI-HOT MIXMATCH AND COMPOSITION CONSISTENCE TRAINING Ziqiang Shi, Liu Liu, Rujie Liu, Fujitsu R&D Center, China ASMSP-1.2: ROBUST DRONE DETECTION FOR ACOUSTIC MONITORING APPLICATIONS .................................... 6 Mattes Ohlenbusch, Aike Ahrens, Christian Rollwage, Fraunhofer Institute for Digital Media Technology, Germany; Jörg Bitzer, Jade Hochschule Wilhelmshaven, Oldenburg, Elsfleth, Germany ASMSP-1.3: UNSUPERVISED DOMAIN ADAPTATION FOR ACOUSTIC SCENE ...........................................................11 CLASSIFICATION USING BAND-WISE STATISTICS MATCHING Alessandro Ilic Mezza, Politecnico di Milano, Italy; Emanuël A. P. Habets, Meinard Müller, International Audio Laboratories Erlangen, Germany; Augusto Sarti, Politecnico di Milano, Italy ASMSP-1.4: SELD-TCN: SOUND EVENT LOCALIZATION & DETECTION VIA TEMPORAL .................................... 16 CONVOLUTIONAL NETWORKS Karim Guirguis, Christoph Schorn, Andre Guntoro, Robert Bosch GmbH, Germany; Sherif Abdulatif, Bin Yang, University of Stuttgart, Germany ASMSP-1.5: LEARNING TO SEPARATE: SOUNDSCAPE CLASSIFICATION USING .................................................... 21 FOREGROUND AND BACKGROUND Dhanunjaya Varma Devalraju, Padmanabhan Rajan, Dileep A.D, Indian Institute of Technology, Mandi, India ASMSP-1.6: PROGRESSIVE TRAINING OF CONVOLUTIONAL NEURAL NETWORKS FOR ................................... 26 ACOUSTIC EVENTS CLASSIFICATION Federico Colangelo, Federica Battisti, Alessandro Neri, Università degli studi Roma Tre, Italy ASMSP-1.7: FEATURE OVERVIEW FOR JOINT MODELING OF SOUND EVENT ........................................................ 31 DETECTION AND LOCALIZATION USING A MICROPHONE ARRAY Daniel Krause, AGH University of Science and Technology, Poland; Archontis Politis, Tampere University, Finland; Konrad Kowalczyk, AGH University of Science and Technology, Poland ASMSP-1.8: ROBUST ACOUSTIC SCENE CLASSIFICATION TO MULTIPLE DEVICES USING ............................... 36 MAXIMUM CLASSIFIER DISCREPANCY AND KNOWLEDGE DISTILLATION Saori Takeyama, Tokyo Institute of Technology, LINE corporation, Japan; Tatsuya Komatsu, LINE corporation, Japan; Koichi Miyazaki, Nagoya University, LINE corporation, Japan; Masahito Togami, LINE corporation, Japan; Shunsuke Ono, Tokyo Institute of Technology, Japan ASMSP-1.9: SOUND EVENT LOCALIZATION AND DETECTION USING CONVOLUTIONAL .................................. 41 RECURRENT NEURAL NETWORKS AND GATED LINEAR UNITS Tatsuya Komatsu, Masahito Togami, Tsubasa Takahashi, LINE Corporation, Japan ASMSP-1.10: AUTOMATIC OBJECT CLASSIFICATION WITH ACTIVE SONAR USING ............................................ 46 UNSUPERVISED ANOMALY DETECTION Pietro Stinco, Giovanni De Magistris, Alessandra Tesei, Kevin D. LePage, NATO STO CMRE - Centre for Maritime Research and Experimentation, Italy ASMSP-2: ASMSP-2: MODELING, ANALYSIS AND SYNTHESIS OF ACOUSTIC ENVIRONMENTS ASMSP-2.1: FAST SOURCE-ROOM-RECEIVER ACOUSTICS MODELING ..................................................................... 51 Yuancheng Luo, Wontak Kim, Amazon, United States xvii ASMSP-2.2: MIRAGE: MULTICHANNEL DATABASE OF ROOM IMPULSE RESPONSES .......................................... 56 MEASURED ON HIGH-RESOLUTION CUBE-SHAPED GRID Jaroslav Cmejla, Tomas Kounovsky, Technical University of Liberec, Czech Republic; Sharon Gannot, Bar-Ilan University, Israel; Zbynek Koldovsky, Technical University of Liberec, Czech Republic; Pinchas Tandeitnik, Bar-Ilan University, Israel ASMSP-2.3: INFERRING THE LOCATION OF REFLECTING SURFACES EXPLOITING ........................................... 61 LOUDSPEAKER DIRECTIVITY Vincenzo Zaccà, Delft University of Technology, Netherlands; Pablo Martínez-Nuevo, Martin Møller, Bang & Olufsen, Denmark; Jorge Martínez, Richard Heusdens, Delft University of Technology, Netherlands ASMSP-2.4: A METHODOLOGY FOR THE ESTIMATION OF PROPAGATION SPEED OF ......................................... 66 LONGITUDINAL WAVES IN TONE WOOD Luca Villa, Mirco Pezzoli, Fabio Antonacci, Augusto Sarti, Politecnico di Milano, Italy ASMSP-2.5: HIGH-RESOLUTION SPEAKER COUNTING IN REVERBERANT ROOMS USING ................................ 71 CRNN WITH AMBISONICS FEATURES Pierre-Amaury Grumiaux, Srdjan Kitic, Orange Labs, France; Laurent Girin, Univ. Grenoble Alpes, GIPSA-lab, Grenoble-INP, CNRS, France; Alexandre Guérin, Orange Labs, France ASMSP-2.6: SPEECH PRIVACY PROTECTION BASED ON OPTIMAL CONTROLLING ............................................. 76 ESTIMATED SPEECH TRANSMISSION INDEX IN NOISY REVERBERANT ENVIRONMENTS suradej Doungpummet, Japan Advanced Institute of Science and Technology, Japan; Phrimphissa Kraikhun, Chatrin Phunruangsakao, Sirindhorn International Institute of Technology, Thammasat University, Thailand; Jessada Karnjana, National Science and Technology Development Agency, Thailand; Masashi Unoki, Japan Advanced Institute of Science and Technology, Japan; Waree Kongprawechnon, Sirindhorn International Institute of Technology, Thammasat University, Thailand ASMSP-2.7: TECHNIQUES IMPROVING THE ROBUSTNESS OF DEEP LEARNING ................................................... 81 MODELS FOR INDUSTRIAL SOUND ANALYSIS David S. Johnson, Fraunhofer Institute for Digital Media Technology (IDMT), Germany; Sascha Grollmisch, Technische Universität Ilmenau, Germany ASMSP-2.8: TYPE/POSITION CLASSIFICATION OF INTER-FLOOR NOISE IN RESIDENTIAL ............................... 86 BUILDINGS WITH A SINGLE MICROPHONE VIA SUPERVISED LEARNING Hwiyong Choi, Haesang Yang, Seungjun Lee, Woojae Seong, Seoul National University, Korea (South) ASMSP-3: ASMSP-3: BIOACOUSTICS AND MEDICAL ACOUSTICS ASMSP-3.1: DEMENTIA CLASSIFICATION USING ACOUSTIC DESCRIPTORS DERIVED ....................................... 91 FROM SUBSAMPLED SIGNALS Ayush Triapthi, Rupayan Chakraborty, Sunil Kumar Kopparapu, TCS Research and Innovation - Mumbai, India ASMSP-3.2: PERFORMANCE REQUIREMENTS FOR COUGH CLASSIFIERS IN ......................................................... 96 REAL-WORLD APPLICATIONS Bert den Brinker, Philips Research, Netherlands; Mara Coman, Fontys University of Applied Sciences, Netherlands; Okke Ouweltjes, Philips Research, Netherlands; Susannah Thackray-Nocera, Michael Crooks, Alyn H. Morice, Hull York Medical School, United Kingdom ASMSP-3.3: WEAK SPEECH SUPERVISION: A CASE STUDY OF DYSARTHRIA SEVERITY .................................. 101 CLASSIFICATION Mirali Purohit, Dhirubhai Ambani Institute of Information and Communication Technology, India; Mihir Parmar, Arizona State University, United States; Maitreya Patel, Harshit Malaviya, Hemant Patil, Dhirubhai Ambani Institute of Information and Communication Technology, India ASMSP-3.4: METHODS TO IMPROVE THE ROBUSTNESS OF RIGHT WHALE DETECTION ................................ 106 USING CNNS IN CHANGING CONDITIONS William Vickers, Ben Milner, Artjom Gorpincenko, University of East Anglia, United Kingdom; Robert Lee, Gardline, United Kingdom xviii ASMSP-3.5: A UNIVERSAL SYSTEM FOR COUGH DETECTION IN DOMESTIC ACOUSTIC ..................................111 ENVIRONMENTS Nikonas Simou, Nikolaos Stefanakis, Foundation for Research and Technology, Greece; Panagiotis Zervas, Hellenic Mediterranean University, Greece ASMSP-3.6: AUTOMATED DYSARTHRIA SEVERITY CLASSIFICATION USING DEEP ............................................116 LEARNING FRAMEWORKS Amlu Anna Joshy, Rajeev Rajan, College of Engineering, Trivandrum, India ASMSP-3.7: JOINTLY LEVERAGING DECORRELATION AND SPARSITY FOR IMPROVED .................................. 121 FEEDBACK CANCELLATION IN HEARING AIDS Kuan-Lin Chen, Ching-Hua Lee, Bhaskar D. Rao, Harinath Garudadri, University of California San Diego, United States ASMSP-4: ASMSP-4: MUSIC SIGNAL ANALYSIS AND PROCESSING ASMSP-4.1: MULTIPITCH TRACKING IN MUSIC SIGNALS USING ECHO STATE ................................................... 126 NETWORKS Peter Steiner, Simon Stone, Peter Birkholz, Technische Universität Dresden, Germany; Azarakhsh Jalalvand, Ghent University -- imec, Germany ASMSP-4.2: HOW LOW CAN YOU GO? REDUCING FREQUENCY AND TIME RESOLUTION ............................... 131 IN CURRENT CNN ARCHITECTURES FOR MUSIC AUTO-TAGGING Andres Ferraro, Dmitry Bogdanov, Universitat Pompeu Fabra, Spain; Jay Ho Jeon, Jason Yoon, Kakao Corp., Korea (South); Xavier Serra, Universitat Pompeu Fabra, Spain ASMSP-4.3: TRANSFER LEARNING FROM SPEECH TO MUSIC: TOWARDS ............................................................. 136 LANGUAGE-SENSITIVE EMOTION RECOGNITION MODELS Juan Sebastián Gómez Cañón, Universitat Pompeu Fabra, Spain; Estefanía