Speaker: Mr. Jaswanth Reddy Katthi
Affiliation: M.Tech. (Res) Alumnus, EE Dept, IISc Bangalore
Date and Time: August 27, 2021 (Friday), 5:45 PM to 6:30 PM
Talk Recording YouTube Link: https://youtu.be/qG0x-eeg79I
Abstract:
The perception of speech and audio is one of the defining features of humans. Much of the brain’s underlying processes as we listen to acoustic signals are unknown, and significant research efforts are needed to unravel them. The non-invasive recording techniques like EEG and MEG are commonly deployed to capture the brain responses to auditory stimuli. But they capture artifacts which distort the stimulus-response analysis, and their effect becomes more evident for naturalistic stimuli. To reduce the noise, pre-processing methods like the canonical correlation analysis (CCA) are prevalently used. However, these methods assume a simplistic linear relationship between the audio features and the EEG responses and therefore, may not alleviate the effect of recorded artifacts. In this talk, we discuss the novel methods using machine learning advances to improve the audio-EEG analysis. We discuss deep learning framework proposed for audio-EEG analysis in intra-subject and inter-subject settings. The deep learning models are trained with a Pearson correlation-based cost function among the stimuli and responses. The deep learning models are regularized for alleviating the effect of the abundant noise present in the EEG recordings. The framework allows us to obtain the optimum audio and EEG representations that are maximally correlated. We discuss their application on speech and music listening tasks, and conclude with a discussion on future directions in audio-EEG analysis.
Biography:
Jaswanth Reddy Katthi has completed his undergrad from Jawaharlal Nehru Technological University, Anantapur in Electronics and Communication Engineering in 2017. He is an M. Tech (Research) student in EE department under the program System Science and Signal Processing, and has recently presented his thesis colloquium talk. Being a part of LEAP lab, he pursued his research under the guidance of Dr. Sriram Ganapathy. Currently, he is a camera systems engineer at Qualcomm Hyderabad’s Multimedia systems division. His research interests involve machine learning, signal processing and cognitive neuroscience.