Data

Cognitive Load with Speech and EGG (CLSE) dataset

Commonwealth Scientific and Industrial Research Organisation
CSIRO
Viewed: [[ro.stat.viewed]] Cited: [[ro.stat.cited]] Accessed: [[ro.stat.accessed]]
ctx_ver=Z39.88-2004&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Adc&rfr_id=info%3Asid%2FANDS&rft_id=info:doi10.25919/bfq8-r737&rft.title=Cognitive Load with Speech and EGG (CLSE) dataset&rft.identifier=https://doi.org/10.25919/bfq8-r737&rft.publisher=Commonwealth Scientific and Industrial Research Organisation&rft.description=The Cognitive Load with Speech and EGG (CLSE) dataset simultaneously records speech and electroglottograph (EGG) data from 18 participants across four sets of tasks: (1) Story reading task, (2) Stroop test with time pressure, (3) Reading span task, and (4) Stroop test with dual task.This dataset was used as basis to the INTERSPEECH 2014 Computational Paralinguistics Challenge (ComParE2014).EGG data were obtained using the Laryngograph device from Laryngograph Ltd. Both speech and EGG were recorded simultaneously at a sampling frequency of 48 kHz and a resolution of 16 bits. These signals were later downsampled to 16 kHz.Access to this dataset for Commercial use is conditional on a separate Agreement and subject to a fee. Contact us for more information.Lineage: This dataset was originally collected by Dr. Tet Fey Yap as part of their Doctoral thesis.&rft.creator=CSIRO &rft.date=2026&rft.edition=v1&rft.relation=https://doi.org/10.26190/unsworks/15406&rft.relation=https://doi.org/10.1016/j.specom.2015.05.007&rft_rights=Creative Commons Attribution-Noncommercial-No Derivatives 4.0 International Licence https://creativecommons.org/licenses/by-nc-nd/4.0/&rft_rights=Access to the data is restricted&rft_rights=All Rights (including copyright) CSIRO 2026.&rft_subject=Cognitive load&rft_subject=Electroglottograph&rft_subject=EGG.&rft_subject=Computational linguistics&rft_subject=Linguistics&rft_subject=LANGUAGE, COMMUNICATION AND CULTURE&rft_subject=Memory and attention&rft_subject=Cognitive and computational psychology&rft_subject=PSYCHOLOGY&rft_subject=Psycholinguistics (incl. speech production and comprehension)&rft_subject=Cognitive and computational psychology not elsewhere classified&rft.type=dataset&rft.language=English Access the data
Cite Saved to MyRDA Save to MyRDA

Licence & Rights:

Non-Derivative Licence view details
CC-BY-NC-ND

Creative Commons Attribution-Noncommercial-No Derivatives 4.0 International Licence
https://creativecommons.org/licenses/by-nc-nd/4.0/

Access to the data is restricted

All Rights (including copyright) CSIRO 2026.

Access:

Open

Contact Information



Full description

The Cognitive Load with Speech and EGG (CLSE) dataset simultaneously records speech and electroglottograph (EGG) data from 18 participants across four sets of tasks: (1) Story reading task, (2) Stroop test with time pressure, (3) Reading span task, and (4) Stroop test with dual task.
This dataset was used as basis to the INTERSPEECH 2014 Computational Paralinguistics Challenge (ComParE2014).
EGG data were obtained using the Laryngograph device from Laryngograph Ltd. Both speech and EGG were recorded simultaneously at a sampling frequency of 48 kHz and a resolution of 16 bits. These signals were later downsampled to 16 kHz.

Access to this dataset for Commercial use is conditional on a separate Agreement and subject to a fee. Contact us for more information.
Lineage: This dataset was originally collected by Dr. Tet Fey Yap as part of their Doctoral thesis.

Available: 2026-02-24

Data time period: 2009-05-01 to 2012-05-01

This dataset is part of a larger collection

Click to explore relationships graph
Help

Related Publications

Subjects
Cognitive and Computational Psychology | Cognitive and Computational Psychology Not Elsewhere Classified | Cognitive load | Computational Linguistics | EGG. | Electroglottograph | Language, Communication and Culture | Linguistics | Memory and Attention | Psychology | Psycholinguistics (Incl. Speech Production and Comprehension) |

User Contributed Tags    

Login to tag this record with meaningful keywords to make it easier to discover

Identifiers
ACN 633 798 857