liu.seSearch for publications in DiVA
Change search
Link to record
Permanent link

Direct link
BETA
Shirnin, Denis
Publications (1 of 1) Show all publications
Shirnin, D., Lyxell, B., Dahlström, Ö., Blomberg, R., Rudner, M., Rönnberg, J. & Signoret, C. (2017). Speech perception in noise: prediction patterns of neural pre-activation in lexical processing. In: : . Paper presented at Fourth International Conference on Cognitive Hearing Science for Communication (CHSCOM2017), Linköping, Sweden,June 18-22, 2017. Swedish Institute for Disability Research, Linköping University, Article ID 65.
Open this publication in new window or tab >>Speech perception in noise: prediction patterns of neural pre-activation in lexical processing
Show others...
2017 (English)Conference paper, Poster (with or without abstract) (Other academic)
Abstract [en]

The purpose of this study is to examine whether the neural correlates of lexical expectations could be used to predict speech in noise perception. We analyse mag-netoencephalography (MEG) data from 20 normal hearing participants, who read a set of couplets (a pair of phrases with rhyming end words) prior to the experiment. During the experiment, the participants are asked to listen to the couplets, whose intelligibility is set to 80%. However, the last word is pronounced with a delay of 1600 ms (i.e. expectation gap) and is masked at 50% of intelligibility. At the end of each couplet, the participants are asked to indicate if the last word was cor-rect, i.e. corresponding to the expected word. Given the oscillatory characteristics of neural patterns of lexical expectations during the expectation gap, can we predict the participant’s actual perception of the last word? In order to approach this re-search question, we aim to identify the correlation patterns between the instances of neural pre-activation, occurring during the interval of the expectation gap and the type of the given answer. According to the sequential design of the experiment, the expectation gap is placed 4400 ms prior to the time interval dedicated to the participant’s answer. Machine Learning approach has been chosen as the main tool for the pattern recognition.

Place, publisher, year, edition, pages
Swedish Institute for Disability Research, Linköping University, 2017
National Category
Psychology (excluding Applied Psychology)
Identifiers
urn:nbn:se:liu:diva-159501 (URN)
Conference
Fourth International Conference on Cognitive Hearing Science for Communication (CHSCOM2017), Linköping, Sweden,June 18-22, 2017
Available from: 2019-08-09 Created: 2019-08-09 Last updated: 2019-08-09Bibliographically approved
Organisations

Search in DiVA

Show all publications