Facial Expression-based AI System for Personalized Music Recommendations

DOI

10.2991/978-94-6463-738-0_23How to use a DOI?

Keywords

Facial Expression Recognition; Personalized Music Recommendations; Emotion-Aware AI; Convolutional Neural Networks (CNNs); Spotify API Integration

Abstract

Face recognition technology has garnered a lot of interest because of its vast range of applications and potential market. Digital video processing, security systems, and many other technological advancements are among the numerous industries in which it is being used. A person’s emotions are also recognized to be more strongly connected to music than any other art form. It has the special power to improve one’s mood. This study introduces an AI system that uses facial expressions to provide emotion-driven, real-time music recommendations. Our work focuses specifically on the evaluation of convolutional neural networks (CNNs) and the use of deep learning techniques for Facial Emotion Recognition. CNNs are selected because of their exceptional performance in image classification tasks and their capacity to automatically extract important features from images. The Spotify API is coupled with an emotion database that maps the identified emotional states to provide music recommendations based on the user’s present mood. The suggested approach exhibits facial emotion recognition accuracy of about 89%. In addition to bridging the gap between artificial intelligence and emotional intelligence, this method redefines user-centric design in multimedia applications.

Copyright

© 2025 The Author(s)

Open Access

Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Download article (PDF)

TY  - CONF
AU  - V. Vijayalakshmi
AU  - Pooja Shrivastav
AU  - Gomathi Thiyagarajan
PY  - 2025
DA  - 2025/06/22
TI  - Facial Expression-based AI System for Personalized Music Recommendations
BT  - Proceedings of the International Conference on Advances and Applications in Artificial Intelligence (ICAAAI 2025)
PB  - Atlantis Press
SP  - 273
EP  - 285
SN  - 1951-6851
UR  - https://doi.org/10.2991/978-94-6463-738-0_23
DO  - 10.2991/978-94-6463-738-0_23
ID  - Vijayalakshmi2025
ER  -