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A Comparison of Temporal Response Function Estimation Methods for Auditory Attention Decoding

Wong, DDE; Fuglsang, S; Hjortkjær, J; Ceolini, E; Slaney, M; de Cheveigné, A; (2018) A Comparison of Temporal Response Function Estimation Methods for Auditory Attention Decoding. bioRxiv: Cold Spring Harbor, Long Island, NY, USA. Green open access

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Abstract

The decoding of selective auditory attention from noninvasive electroencephalogram (EEG) data is of interest in brain computer interface and auditory perception research. The current state-of-the-art approaches for decoding the attentional selection of listeners are based on temporal response functions (TRFs). In the current context, a TRF is a function that facilitates a mapping between features of sound streams and EEG responses. It has been shown that when the envelope of attended speech and EEG responses are used to derive TRF mapping functions, the TRF model predictions can be used to discriminate between attended and unattended talkers. However, the predictive performance of the TRF models is dependent on how the TRF model parameters are estimated. There exist a number of TRF estimation methods that have been published, along with a variety of datasets. It is currently unclear if any of these methods perform better than others, as they have not yet been compared side by side on a single standardized dataset in a controlled fashion. Here, we present a comparative study of the ability of different TRF estimation methods to classify attended speakers from multi-channel EEG data. The performance of the TRF estimation methods is evaluated using different performance metrics on a set of labeled EEG data from 18 subjects listening to mixtures of two speech streams.

Type: Working / discussion paper
Title: A Comparison of Temporal Response Function Estimation Methods for Auditory Attention Decoding
Open access status: An open access version is available from UCL Discovery
DOI: 10.1101/281345
Publisher version: https://doi.org/10.1101/281345
Language: English
Additional information: The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC-ND 4.0 International license.
UCL classification: UCL
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences > The Ear Institute
URI: https://discovery.ucl.ac.uk/id/eprint/10067230
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