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A System Identification Approach to Determining Listening Attention from EEG Signals
Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, Faculty of Science & Engineering.
Linköping University, Department of Behavioural Sciences and Learning, Disability Research. Linköping University, Faculty of Arts and Sciences. Linköping University, The Swedish Institute for Disability Research. Linköping University, Department of Clinical and Experimental Medicine, Technical Audiology. Eriksholm Research Centre, Oticon A/S, 20 Rortangvej, Snekkersten, Denmark.
Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, Faculty of Science & Engineering.
2016 (English)Conference paper (Refereed)
Abstract [en]

We still have very little knowledge about how ourbrains decouple different sound sources, which is known assolving the cocktail party problem. Several approaches; includingERP, time-frequency analysis and, more recently, regression andstimulus reconstruction approaches; have been suggested forsolving this problem. In this work, we study the problem ofcorrelating of EEG signals to different sets of sound sources withthe goal of identifying the single source to which the listener isattending. Here, we propose a method for finding the number ofparameters needed in a regression model to avoid overlearning,which is necessary for determining the attended sound sourcewith high confidence in order to solve the cocktail party problem.

Place, publisher, year, edition, pages
2016. 31-35 p.
Keyword [en]
attention, cocktail party, linear regression (LR), finite impulse response (FIR), multivariable model, sound, EEG
National Category
Control Engineering
Identifiers
URN: urn:nbn:se:liu:diva-130732OAI: oai:DiVA.org:liu-130732DiVA: diva2:954379
Conference
2016 European Signal Processing Conference (EUSIPCO 2016)
Available from: 2016-08-22 Created: 2016-08-22 Last updated: 2016-08-30

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Alickovic, EminaLunner, ThomasGustafsson, Fredrik
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