Skip to main content

Lund University Publications

LUND UNIVERSITY LIBRARIES

Novel bias-reduced coherence measure for EEG-based speech tracking in listeners with hearing impairment

Keding, Oskar LU ; Alickovic, Emina ; Skoglund, Martin A. and Sandsten, Maria LU (2024) In Frontiers in Neuroscience 18.
Abstract

In the literature, auditory attention is explored through neural speech tracking, primarily entailing modeling and analyzing electroencephalography (EEG) responses to natural speech via linear filtering. Our study takes a novel approach, introducing an enhanced coherence estimation technique to assess the strength of neural speech tracking. This enables effective discrimination between attended and ignored speech. To mitigate the impact of colored noise in EEG, we address two biases–overall coherence-level bias and spectral peak-shifting bias. In a listening study involving 32 participants with hearing impairment, tasked with attending to competing talkers in background noise, our coherence-based method effectively discerns EEG... (More)

In the literature, auditory attention is explored through neural speech tracking, primarily entailing modeling and analyzing electroencephalography (EEG) responses to natural speech via linear filtering. Our study takes a novel approach, introducing an enhanced coherence estimation technique to assess the strength of neural speech tracking. This enables effective discrimination between attended and ignored speech. To mitigate the impact of colored noise in EEG, we address two biases–overall coherence-level bias and spectral peak-shifting bias. In a listening study involving 32 participants with hearing impairment, tasked with attending to competing talkers in background noise, our coherence-based method effectively discerns EEG representations of attended and ignored speech. We comprehensively analyze frequency bands, individual frequencies, and EEG channels. Frequency bands of importance are shown to be delta, theta and alpha, and the important EEG channels are the central. Lastly, we showcase coherence differences across different noise reduction settings implemented in hearing aids (HAs), underscoring our method's potential to objectively assess auditory attention and enhance HA efficacy.

(Less)
Please use this url to cite or link to this publication:
author
; ; and
organization
publishing date
type
Contribution to journal
publication status
published
subject
keywords
auditory attention, coherence, EEG, hearing impairment, multitapers, neural speech tracking
in
Frontiers in Neuroscience
volume
18
article number
1415397
publisher
Frontiers Media S. A.
external identifiers
  • scopus:85210076435
  • pmid:39568664
ISSN
1662-4548
DOI
10.3389/fnins.2024.1415397
language
English
LU publication?
yes
id
a07a97aa-3d77-411e-9705-c6fe0b623e9f
date added to LUP
2025-01-15 14:39:59
date last changed
2025-07-17 05:48:16
@article{a07a97aa-3d77-411e-9705-c6fe0b623e9f,
  abstract     = {{<p>In the literature, auditory attention is explored through neural speech tracking, primarily entailing modeling and analyzing electroencephalography (EEG) responses to natural speech via linear filtering. Our study takes a novel approach, introducing an enhanced coherence estimation technique to assess the strength of neural speech tracking. This enables effective discrimination between attended and ignored speech. To mitigate the impact of colored noise in EEG, we address two biases–overall coherence-level bias and spectral peak-shifting bias. In a listening study involving 32 participants with hearing impairment, tasked with attending to competing talkers in background noise, our coherence-based method effectively discerns EEG representations of attended and ignored speech. We comprehensively analyze frequency bands, individual frequencies, and EEG channels. Frequency bands of importance are shown to be delta, theta and alpha, and the important EEG channels are the central. Lastly, we showcase coherence differences across different noise reduction settings implemented in hearing aids (HAs), underscoring our method's potential to objectively assess auditory attention and enhance HA efficacy.</p>}},
  author       = {{Keding, Oskar and Alickovic, Emina and Skoglund, Martin A. and Sandsten, Maria}},
  issn         = {{1662-4548}},
  keywords     = {{auditory attention; coherence; EEG; hearing impairment; multitapers; neural speech tracking}},
  language     = {{eng}},
  publisher    = {{Frontiers Media S. A.}},
  series       = {{Frontiers in Neuroscience}},
  title        = {{Novel bias-reduced coherence measure for EEG-based speech tracking in listeners with hearing impairment}},
  url          = {{http://dx.doi.org/10.3389/fnins.2024.1415397}},
  doi          = {{10.3389/fnins.2024.1415397}},
  volume       = {{18}},
  year         = {{2024}},
}