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Hits 1 – 3 of 3
1
Investigating the fit between phonological feature systems and brain responses to speech using EEG ...
McCloy, Daniel R.
;
Lee, Adrian K. C.
. - : Taylor & Francis, 2019
Abstract:
This paper describes a technique to assess the correspondence between patterns of similarity in the brain's response to speech sounds and the patterns of similarity encoded in phonological feature systems, by quantifying the recoverability of phonological features from the neural data using supervised learning. The technique is applied to EEG recordings collected during passive listening to consonant-vowel syllables. Three published phonological feature systems are compared, and are shown to differ in their ability to recover certain speech sound contrasts from the neural data. For the phonological feature system that best reflects patterns of similarity in the neural data, a leave-one-out analysis indicates some consistency across subjects in which features have greatest impact on the fit, but considerable across-subject heterogeneity remains in the rank ordering of features in this regard. ...
Keyword:
111714 Mental Health
;
69999 Biological Sciences not elsewhere classified
;
80699 Information Systems not elsewhere classified
;
FOS Biological sciences
;
FOS Computer and information sciences
;
FOS Health sciences
;
Neuroscience
;
Space Science
URL:
https://dx.doi.org/10.6084/m9.figshare.7614068
https://tandf.figshare.com/articles/Investigating_the_fit_between_phonological_feature_systems_and_brain_responses_to_speech_using_EEG/7614068
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2
Investigating the fit between phonological feature systems and brain responses to speech using EEG ...
McCloy, Daniel R.
;
Lee, Adrian K. C.
. - : Taylor & Francis, 2019
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3
Investigating the fit between phonological feature systems and brain responses to speech using EEG ...
McCloy, Daniel R.
;
Lee, Adrian K. C.
. - : Taylor & Francis, 2019
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