Expanding the Singular Channel - MODALINK: A Generalized Automated Multimodal Dataset Generation Workflow for Emotion Recognition

Amany H. AbouEl-Naga, May Hussien, Wolfgang Minker, Mohammed Salem, Nada Sharaf

2025

Abstract

Human communication relies deeply on the emotional states of the individuals involved. The process of identifying and processing emotions in the human brain is inherently multimodal. With recent advancements in artificial intelligence and deep learning, fields like affective computing and human-computer interaction have witnessed tremendous progress. This has shifted the focus from unimodal emotion recognition systems to mul-timodal systems that comprehend and analyze emotions across multiple channels, such as facial expressions, speech, text, and physiological signals, to enhance emotion classification accuracy. Despite these advancements, the availability of datasets combining two or more modalities remains limited. Furthermore, very few datasets have been introduced for the Arabic language, despite its widespread use (Safwat et al., 2023; Akila et al., 2015). In this paper, MODALINK, an automated workflow to generate the first novel Egyptian-Arabic dialect dataset integrating visual, audio, and text modalities is proposed. Preliminary testing phases of the proposed workflow demonstrate its ability to generate synchronized modalities efficiently and in a timely manner.

Paper Citation

in Harvard Style

AbouEl-Naga A., Hussien M., Minker W., Salem M. and Sharaf N. (2025). Expanding the Singular Channel - MODALINK: A Generalized Automated Multimodal Dataset Generation Workflow for Emotion Recognition. In Proceedings of the 14th International Conference on Data Science, Technology and Applications - Volume 1: DATA; ISBN 978-989-758-758-0, SciTePress, pages 415-422. DOI: 10.5220/0013520100003967

in Bibtex Style

@conference{data25,
author={Amany AbouEl-Naga and May Hussien and Wolfgang Minker and Mohammed Salem and Nada Sharaf},
title={Expanding the Singular Channel - MODALINK: A Generalized Automated Multimodal Dataset Generation Workflow for Emotion Recognition},
booktitle={Proceedings of the 14th International Conference on Data Science, Technology and Applications - Volume 1: DATA},
year={2025},
pages={415-422},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0013520100003967},
isbn={978-989-758-758-0},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 14th International Conference on Data Science, Technology and Applications - Volume 1: DATA
TI - Expanding the Singular Channel - MODALINK: A Generalized Automated Multimodal Dataset Generation Workflow for Emotion Recognition
SN - 978-989-758-758-0
AU - AbouEl-Naga A.
AU - Hussien M.
AU - Minker W.
AU - Salem M.
AU - Sharaf N.
PY - 2025
SP - 415
EP - 422
DO - 10.5220/0013520100003967
PB - SciTePress