Distinguished Lectures in Humanities : attentive listening by humans and machines

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.
Event date: 4/11/2025
Speaker: Prof. LI Haizhou
Hosted by: Faculty of Humanities