Distinguished Lectures in Humanities: Attentive Listening by Humans and Machines

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. As discovered in neuroscience and psychoacoustics, the auditory attention is achieved by a modulation of top-down and bottom-up attention. 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 will also discuss the computational auditory models, technical challenges and the recent advances in the field.

About the speaker

Professor Haizhou LI is a Fellow of the Singapore Academy of Engineering, a Fellow of the IEEE, and a Fellow of International Speech Communication Association. He is currently the Dean of the School of Artificial Intelligence and Presidential Chair Professor at The Chinese University of Hong Kong, Shenzhen. He also serves as Adjunct Professor at the National University of Singapore and U Bremen Excellence Chair Professor at the University of Bremen, Germany.

Professor LI has made outstanding contributions to speech recognition and natural language processing. He has led the development of multiple major technology deployments, including the voiceprint recognition engine for Lenovo’s A586 smartphone in 2012, and the music search engine for Baidu Music in 2013. He was the Editor-in-Chief of IEEE/ACM Transactions on Audio, Speech and Language Processing, the President of International Speech Communication Association, and a Vice President of IEEE Signal Processing Society.