Abstract

The brain empowers humans with remarkable abilities to navigate their acoustic environment in highly degraded conditions. This seemingly trivial task for normal hearing listeners is extremely challenging for individuals with auditory pathway disorders, and has proven very difficult to model and implement algorithmically in machines. In this talk, I will present the result of an interdisciplinary research effort where invasive and non-invasive neural recordings from human auditory cortex and reverse-engineering methodologies are used to determine the representational and computational properties of speech processing in the human auditory cortex. These findings lead to new biologically informed models incorporating the functional properties of neural mechanisms with potential to decrease the performance gap between biological and artificial computing. A better understanding of the neural mechanisms involved in speech processing can greatly impact the current models of speech perception and lead to human-like automatic speech processing technologies.

Biography

Nima Mesgarani is an assistant professor of Electrical Engineering at Columbia University. He received his Ph.D. from University of Maryland where he worked on neuromorphic speech technologies and neurophysiology of mammalian auditory cortex. He was a postdoctoral scholar in Center for Language and Speech Processing at Johns Hopkins University, and the neurosurgery department of University of California San Francisco before joining Columbia in fall 2013. He was named a Pew Scholar for Innovative Biomedical Research in 2015, and received the National Science Foundation Early Career Award in 2016.