BESST Cognitive Load Dataset

The BESST Cognitive Load Dataset is a multimodal dataset designed to study speech production under stress and cognitive load. It contains empirical data collected using the BESST experimental protocol, featuring 79 cases and 8 signals. This dataset is aimed at advancing machine learning models for stress estimation and pre-emptive intervention systems.

Table of Contents

1. Overview
2. Dataset Features
3. Experimental Protocol
4. Getting Started
5. Usage
6. Citation
7. License

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Overview

Stress can impair cognitive functions, impacting critical areas like aviation, surgery, and public safety. The BESST Cognitive Load Dataset provides multimodal data for developing advanced machine learning models to identify stress and cognitive load from speech. This dataset bridges the gap in available resources, offering high-quality data annotated with subjective self-determined and objective biological labels.

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Dataset Features

Field	Type	Description
id	string	Unique identifier for each sample.
audio	Audio	Path to the audio file (supports resampling).
start	int32	Start time of the segment (in seconds).
end	int32	End time of the segment (in seconds).
cognitive_load	ClassLabel	Cognitive load level (low, medium, high).

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Experimental Protocol

The BESST protocol was used to collect data under controlled conditions. Participants performed tasks designed to induce cognitive load and stress while speech, physiological, and behavioral signals were recorded.

Signals Captured:

1. Speech signals (close-talk microphones)
2. ECG+Heart rate and variability
3. Skin conductance
4. Task performance metrics
5. Reaction times
6. Other relevant behavioral data

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Getting Started

Prerequisites

• Python 3.7 or later
• Hugging Face datasets library: pip install datasets

Installation

Clone the repository:

git clone https://github.com/BUTSpeechFIT/besst-dataset.git
cd dataset-dataset

Usage

Loading the Dataset Load the dataset using Hugging Face's datasets library:

from datasets import load_dataset
# Load cognitive-load dataset, audio-video subset, split variant 'a'
dataset = load_dataset(
    "besst_dataset",
    name="cognitive-load_audio-video_a",
    data_dir="/path/to/data",
)

Citation

If you use this dataset in your research, please cite it as follows:

@article{Pesan2024,
          title = {Speech production under stress for machine learning: multimodal dataset of 79 cases and 8 signals},
          volume = {11},
          ISSN = {2052-4463},
          url = {http://dx.doi.org/10.1038/s41597-024-03991-w},
          DOI = {10.1038/s41597-024-03991-w},
          number = {1},
          journal = {Scientific Data},
          publisher = {Springer Science and Business Media LLC},
          author = {Pešán,  Jan and Juřík,  Vojtěch and Ružičková,  Alexandra and Svoboda,  Vojtěch and Janoušek,  Oto and Němcová,  Andrea and Bojanovská,  Hana and Aldabaghová,  Jasmína and Kyslík,  Filip and Vodičková,  Kateřina and Sodomová,  Adéla and Bartys,  Patrik and Chudý,  Peter and Černocký,  Jan},
          year = {2024},
          month = nov
        }

License

See: speech.fit.vut.cz/software/besst