A System Identification Approach to Determining Listening Attention from EEG Signals
2016 (engelsk)Inngår i: 2016 24TH EUROPEAN SIGNAL PROCESSING CONFERENCE (EUSIPCO), IEEE , 2016, s. 31-35Konferansepaper, Publicerat paper (Fagfellevurdert)
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.
sted, utgiver, år, opplag, sider
IEEE , 2016. s. 31-35
Serie
European Signal Processing Conference, ISSN 2076-1465
Emneord [en]
attention, cocktail party, linear regression (LR), finite impulse response (FIR), multivariable model, sound, EEG
HSV kategori
Identifikatorer
URN: urn:nbn:se:liu:diva-130732DOI: 10.1109/EUSIPCO.2016.7760204ISI: 000391891900007ISBN: 978-0-9928-6265-7 (digital)ISBN: 978-1-5090-1891-8 (tryckt)OAI: oai:DiVA.org:liu-130732DiVA, id: diva2:954379
Konferanse
24th European Signal Processing Conference (EUSIPCO), Aug 28-Sep 2, 2016. Budapest, Hungary
2016-08-222016-08-222017-02-15