Publication Details
BESST Dataset: A Multimodal Resource for Speech-based Stress Detection and Analysis
Juřík Vojtěch (ICAECS FCE BUT)
Karafiát Martin, Ing., Ph.D. (DCGM FIT BUT)
Černocký Jan, prof. Dr. Ing. (DCGM FIT BUT)
BESST dataset, stress recognition, multimodal data, speech research, physiological signals, cognitive load, speech production
The Brno Extended Stress and Speech Test (BESST) dataset is a new resource for the speech research community, offering multimodal audiovisual, physiological and psychological data that enable investigations into the interplay between stress and speech. In this paper, we introduce the BESST dataset and provide a details of its design, collection protocols, and technical aspects. The dataset comprises speech samples, physiologi- cal signals (including electrocardiogram, electrodermal activity, skin temperature, and acceleration data), and video recordings from 90 subjects performing stress-inducing tasks. It comprises 16.9 hours of clean Czech speech data, averaging 15 minutes of clean speech per participant. The data collection procedure involves the induction of cognitive and physical stress induced by Reading Span task (RSPAN) and Hand Immersion (HIT) task respectively. The BESST dataset was collected under stringent ethical standards and is accessible for research and development.
@INPROCEEDINGS{FITPUB13324,
author = "Jan Pe\v{s}\'{a}n and Vojt\v{e}ch Ju\v{r}\'{i}k and Martin Karafi\'{a}t and Jan \v{C}ernock\'{y}",
title = "BESST Dataset: A Multimodal Resource for Speech-based Stress Detection and Analysis",
pages = "1355--1359",
booktitle = "Proceedings of Interspeech 2024",
journal = "Proceedings of Interspeech - on-line",
volume = 2024,
number = 9,
year = 2024,
location = "Kos, GR",
publisher = "International Speech Communication Association",
ISSN = "1990-9772",
doi = "10.21437/Interspeech.2024-42",
language = "english",
url = "https://www.fit.vut.cz/research/publication/13324"
}