Analysing the Impact of Images and Text for Predicting Human Creativity Through Encoders

Amaia Pikatza-Huerga, Pablo Matanzas de Luis, Miguel Fernandez-De-retana Uribe, Javier Peña Lasa, Unai Zulaika, Aitor Almeida

2025

Abstract

This study explores the application of multimodal machine learning techniques to evaluate the originality and complexity of drawings. Traditional approaches in creativity assessment have primarily focused on visual analysis, often neglecting the potential insights derived from accompanying textual descriptions. The research assesses four target features: drawings’ originality, flexibility and elaboration level, and titles’ creativity, all labelled by expert psychologists. The research compares different image encoding and text embeddings to examine the effectiveness and impact of individual and combined modalities. The results indicate that incorporating textual information enhances the predictive accuracy for all features, suggesting that text provides valuable contextual insights that images alone may overlook. This work demonstrates the importance of a multimodal approach in creativity assessment, paving the way for more comprehensive and nuanced evaluations of artistic expression.

Paper Citation

in Harvard Style

Pikatza-Huerga A., Matanzas de Luis P., Uribe M., Lasa J., Zulaika U. and Almeida A. (2025). Analysing the Impact of Images and Text for Predicting Human Creativity Through Encoders. In Proceedings of the 11th International Conference on Information and Communication Technologies for Ageing Well and e-Health - Volume 1: ICT4AWE; ISBN 978-989-758-743-6, SciTePress, pages 15-24. DOI: 10.5220/0013203600003938

in Bibtex Style

@conference{ict4awe25,
author={Amaia Pikatza-Huerga and Pablo Matanzas de Luis and Miguel Uribe and Javier Lasa and Unai Zulaika and Aitor Almeida},
title={Analysing the Impact of Images and Text for Predicting Human Creativity Through Encoders},
booktitle={Proceedings of the 11th International Conference on Information and Communication Technologies for Ageing Well and e-Health - Volume 1: ICT4AWE},
year={2025},
pages={15-24},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0013203600003938},
isbn={978-989-758-743-6},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 11th International Conference on Information and Communication Technologies for Ageing Well and e-Health - Volume 1: ICT4AWE
TI - Analysing the Impact of Images and Text for Predicting Human Creativity Through Encoders
SN - 978-989-758-743-6
AU - Pikatza-Huerga A.
AU - Matanzas de Luis P.
AU - Uribe M.
AU - Lasa J.
AU - Zulaika U.
AU - Almeida A.
PY - 2025
SP - 15
EP - 24
DO - 10.5220/0013203600003938
PB - SciTePress