Prof. Haizhou Li
National University of Singapore, Singapore
Haizhou Li is a Presidential Chair Professor and Associate Dean (Research) at the School of Data Science, The Chinese University of Hong Kong, Shenzhen, China. Dr. Li is also with the Department of Electrical and Computer Engineering, National University of Singapore (NUS), Singapore.
Dr. Li was the recipient of National Infocomm Awards 2002, Institution of Engineers Singapore (IES) Prestigious Engineering Achievement Award 2013 and 2015, President's Technology Award 2013, and MTI Innovation Activist Gold Award 2015 in Singapore. He was named one of the two Nokia Visiting Professors in 2009 by Nokia Foundation, IEEE Fellow in 2014 for leadership in multilingual, speaker and language recognition, ISCA Fellow in 2018 for contributions to multilingual speech information processing, and Bremen Excellence Chair Professor in 2019. Dr. Li is a Fellow of Academy of Engineering Singapore.
Speech Title: Seeing to Hear Better
Abstract: Humans have a remarkable ability to pay their auditory attention only to a sound source of interest, that we call selective auditory attention, in a multi-talker environment or a Cocktail Party. However, signal processing approach to speech separation and/or speaker extraction from multi-talker speech remains a challenge for machines. In this talk, we study the deep learning solutions to monaural speech separation and speaker extraction that enable selective auditory attention. We review the findings from human audio-visual speech perception to motivate the design of speech perception algorithms. We introduce their applications in speech enhancement, speaker extraction, and speech recognition. We will also discuss the computational auditory models, technical challenges and the recent advances in the field.
Prof. De-Shuang Huang
Tongji University, China
De-Shuang Huang is a Professor in Department of Computer Science and Director of Institute of Machine Learning and Systems Biology at Tongji University, China. He is currently the Fellow of the International Association of Pattern Recognition (IAPR Fellow), Fellow of the IEEE (IEEE Fellow) and Senior Member of the INNS, Bioinformatics and Bioengineering Technical Committee Member of IEEE CIS, Neural Networks Technical Committee Member of IEEE CIS, the member of the INNS, Co-Chair of the Big Data Analytics section within INNS, and associated editors of IEEE/ACM Transactions on Computational Biology & Bioinformatics, and Neural Networks, etc. He founded the International Conference on Intelligent Computing (ICIC) in 2005. ICIC has since been successfully held annually with him serving as General or Steering Committee Chair. He also served as the 2015 International Joint Conference on Neural Networks (IJCNN 2015) General Chair, July 12-17, 2015, Killarney, Ireland, the 2014 11th IEEE Computational Intelligence in Bioinformatics and Computational Biology Conference (IEEE-CIBCBC) Program Committee Chair, May 21-24, 2014, Honolulu, USA. He has published over 470 papers in international journals, international conferences proceedings, and book chapters. Particularly, he has published over 230 SCI indexed papers. His Google Scholar citation number is over 18300 times and H index 73. His main research interest includes neural networks, pattern recognition and bioinformatics.
Prof. Alexander Gammerman
Royal Holloway, University of London, UK
Professor Gammerman's current research interest lies in machine learning and, in particular, in the development of conformal predictors -- a set of novel machine learning techniques that guarantee the validity of prediction. Areas in which these techniques have been applied include medical diagnosis, drug design, forensic science, proteomics, genomics, environment, and information security. He has published about two hundred research papers and several books on computational learning and probabilistic inference.
Professor Gammerman is a Fellow of the Royal Statistical Society and a Fellow of the Royal Society of Arts. He chaired and participated in organizing committees of many international conferences and workshops on Machine Learning and Bayesian methods in Europe, Russia and in the United States. He was also a member of the editorial boards of the Law, Probability and Risk journal (2002-2009) and the Computer Journal (2003-2008). He has held visiting and honorary professorships from several universities in Europe and USA. Further details can be found at http://cml.rhul.ac.uk