Emotionalyzer: Player's Facial Emotion Recognition ML Model for Video Game Testing Automation

Rebeca Bravo-Navarro, Luis Pineda-Knox, Willy Ugarte

2025

Abstract

In video game development, the play testing phase is crucial for evaluating and optimizing user perception before launch. These tests are often costly and require significant time investment, as they are conducted by experts observing gameplay sessions, which makes capturing real-time data, such as facial and bodily expressions, challenging. Additionally, many independent studies lack the necessary resources to conduct professional testing. Therefore, smaller developers need more cost-effective and time-efficient alternatives to improve their products and streamline the development process. This project aims to develop a real-time facial emotion recognition model using machine learning, which will be integrated into an application that records the player’s emotions during the gameplay session. It seeks to benefit Peruvian indie companies by reducing costs and time associated with traditional testing and providing a more precise and detailed evaluation of the user experience. Additionally, the use of machine learning technology ensures continuous adaptation and progressive improvements in the model over time.

Paper Citation

in Harvard Style

Bravo-Navarro R., Pineda-Knox L. and Ugarte W. (2025). Emotionalyzer: Player's Facial Emotion Recognition ML Model for Video Game Testing Automation. In Proceedings of the 27th International Conference on Enterprise Information Systems - Volume 1: ICEIS; ISBN 978-989-758-749-8, SciTePress, pages 937-943. DOI: 10.5220/0013439400003929

in Bibtex Style

@conference{iceis25,
author={Rebeca Bravo-Navarro and Luis Pineda-Knox and Willy Ugarte},
title={Emotionalyzer: Player's Facial Emotion Recognition ML Model for Video Game Testing Automation},
booktitle={Proceedings of the 27th International Conference on Enterprise Information Systems - Volume 1: ICEIS},
year={2025},
pages={937-943},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0013439400003929},
isbn={978-989-758-749-8},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 27th International Conference on Enterprise Information Systems - Volume 1: ICEIS
TI - Emotionalyzer: Player's Facial Emotion Recognition ML Model for Video Game Testing Automation
SN - 978-989-758-749-8
AU - Bravo-Navarro R.
AU - Pineda-Knox L.
AU - Ugarte W.
PY - 2025
SP - 937
EP - 943
DO - 10.5220/0013439400003929
PB - SciTePress