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SLHS Brown Bag (02/24/20) - Subong Kim (Univ. of Iowa)

SLHS Brown Bag (02/24/20) - Subong Kim (Univ. of Iowa)

Author: M. Heinz
Event Date: February 24, 2020
Hosted By: Hari Bharadwaj
Time: 12:30-1:30
Location: LYLE1150
Contact Name: Hari Bharadwaj
Contact Email: hbharadw@purdue.edu
Open To: All
Priority: No
School or Program: Non-Engineering
College Calendar: Show
Subong Kim (Univ. of Iowa) will present the SLHS Brown Bag Seminar, entitled "Audiology meets neuroscience: Neural correlates of hearing remediation efficacy" on February 24th at 1230-120 in LYLE 1150.

 

 

SLHS BROWN BAG SEMINAR SERIES

 

Title:  Audiology meets neuroscience: Neural correlates of hearing remediation efficacy

Speaker: Subong Kim, Ph.D. candidate, Speech and Hearing Science, University of Iowa

 

Date: February 24, 2020

Time: 12:30 – 1:20 pm

Location: LYLE 1150

 

Abstract:

In current audiology clinics, hearing intervention services are provided in the way of maximizing audibility. However, because speech perception does not solely depend on audibility, the treatment based on the audibility maximization does not always optimize the speech-perception outcomes of hearing remediation. Thus, my Ph.D. research aimed to explore a mechanistic approach to better diagnose or improve speech perception outcomes through personalized hearing interventions. First, I studied the neural mechanisms underlying speech-in-noise recognition. I explored how the spatiotemporal pattern of brain activity changes in relation to the change in listening conditions. Then, I demonstrated that different ability to extract speech out of background noise drives individual differences in speech perception outcomes. In a follow-up study, when the noise was attenuated using a noise reduction algorithm applied in hearing aids that necessarily involved spectral distortion, the cortical activity showed the consistent spatiotemporal pattern of efficient speech processing. Also, listeners who were not successful in extracting speech from background noise appreciated the noise reduction algorithm more, which indicates that the hearing aid configuration can be optimized by looking at each individual’s speech processing mechanisms. Lastly, I demonstrated that selective attention training enhances listeners’ ability to extract speech from noise, which in turn improves speech-in-noise recognition performance.

 

 

Related Link: https://www.subongkim.com/