The University of Southampton
University of Southampton Institutional Repository

Dataset in support of the Southampton doctoral thesis 'Predicting behavioural speech reception threshold using cortical responses to continuous sound'

Dataset in support of the Southampton doctoral thesis 'Predicting behavioural speech reception threshold using cortical responses to continuous sound'
Dataset in support of the Southampton doctoral thesis 'Predicting behavioural speech reception threshold using cortical responses to continuous sound'
The dataset includes EEG responses to continuous speech, modulated noise, and repeating /da/ stimuli under different background noise conditions (SIN_EEG and SIN_EEG_Da). The EEG files are raw data saved in Biosemi .bdf format. These files can be loaded into software such as MATLAB using the EEGLAB package or Python using the MNE package. The sounds used to generate EEG responses are in .wav format (SIN_Stimuli). These sounds consist of continuous speech, noise modulated by the speech envelope, and short /da/ syllable. SIN_SRT consists of percentage word correct scores from the Matrix test. These scores were used to estimate the participants' speech reception threshold. SIN_EEG_python_script contains examples of EEG data processing. SIN_Stimuli_Order contains information about the order of stimuli and SNR conditions presented to each participant. SIN_Participant_Information and SIN_Consent_Form are the participant information sheet and blank consent form.
University of Southampton
Deoisres, Suwijak
e454d5e5-c7c3-4027-bf4e-203c65a4e6cf
Simpson, David
53674880-f381-4cc9-8505-6a97eeac3c2a
Bell, Steven
91de0801-d2b7-44ba-8e8e-523e672aed8a
Deoisres, Suwijak
e454d5e5-c7c3-4027-bf4e-203c65a4e6cf
Simpson, David
53674880-f381-4cc9-8505-6a97eeac3c2a
Bell, Steven
91de0801-d2b7-44ba-8e8e-523e672aed8a

Deoisres, Suwijak (2023) Dataset in support of the Southampton doctoral thesis 'Predicting behavioural speech reception threshold using cortical responses to continuous sound'. University of Southampton doi:10.5258/SOTON/D2578 [Dataset]

Record type: Dataset

Abstract

The dataset includes EEG responses to continuous speech, modulated noise, and repeating /da/ stimuli under different background noise conditions (SIN_EEG and SIN_EEG_Da). The EEG files are raw data saved in Biosemi .bdf format. These files can be loaded into software such as MATLAB using the EEGLAB package or Python using the MNE package. The sounds used to generate EEG responses are in .wav format (SIN_Stimuli). These sounds consist of continuous speech, noise modulated by the speech envelope, and short /da/ syllable. SIN_SRT consists of percentage word correct scores from the Matrix test. These scores were used to estimate the participants' speech reception threshold. SIN_EEG_python_script contains examples of EEG data processing. SIN_Stimuli_Order contains information about the order of stimuli and SNR conditions presented to each participant. SIN_Participant_Information and SIN_Consent_Form are the participant information sheet and blank consent form.

Text
SIN_README.txt - Text
Available under License Creative Commons Attribution.
Download (7kB)
Archive
SIN_EEG_python_script.rar - Dataset
Available under License Creative Commons Attribution.
Download (38kB)
Archive
SIN_SRT.rar - Dataset
Available under License Creative Commons Attribution.
Download (130kB)
Archive
SIN_Stimuli_Order.rar - Dataset
Available under License Creative Commons Attribution.
Download (15kB)
Archive
SIN_Stimuli.rar - Dataset
Available under License Creative Commons Attribution.
Download (289MB)
Archive
SIN_EEG_S1_S7.rar - Dataset
Available under License Creative Commons Attribution.
Download (3GB)
Archive
SIN_EEG_S8_S14.rar - Dataset
Available under License Creative Commons Attribution.
Download (3GB)
Archive
SIN_EEG_S15_S19.rar - Dataset
Available under License Creative Commons Attribution.
Download (2GB)
Archive
SIN_EEG_S20_S22.rar - Dataset
Available under License Creative Commons Attribution.
Download (1GB)
Archive
SIN_EEG_Da.rar - Dataset
Available under License Creative Commons Attribution.
Download (1GB)
Text
SIN_Participant_Information.pdf - Dataset
Available under License Creative Commons Attribution.
Download (111kB)
Text
SIN_Consent_Form.pdf - Dataset
Available under License Creative Commons Attribution.
Download (59kB)

Show all 12 downloads.

More information

Published date: March 2023

Identifiers

Local EPrints ID: 476402
URI: http://eprints.soton.ac.uk/id/eprint/476402
PURE UUID: 4e51020b-ba13-4b44-8fde-cc6d6c49bd70
ORCID for Suwijak Deoisres: ORCID iD orcid.org/0000-0003-1384-3632
ORCID for David Simpson: ORCID iD orcid.org/0000-0001-9072-5088

Catalogue record

Date deposited: 20 Apr 2023 16:44
Last modified: 06 May 2023 02:00

Export record

Altmetrics

Contributors

Creator: Suwijak Deoisres ORCID iD
Research team head: David Simpson ORCID iD
Research team head: Steven Bell

Download statistics

Downloads from ePrints over the past year. Other digital versions may also be available to download e.g. from the publisher's website.

View more statistics

Atom RSS 1.0 RSS 2.0

Contact ePrints Soton: eprints@soton.ac.uk

ePrints Soton supports OAI 2.0 with a base URL of http://eprints.soton.ac.uk/cgi/oai2

This repository has been built using EPrints software, developed at the University of Southampton, but available to everyone to use.

We use cookies to ensure that we give you the best experience on our website. If you continue without changing your settings, we will assume that you are happy to receive cookies on the University of Southampton website.

×