A Multimodal Approach for Emotion Detection through Facial Expressions, Recommending Movies and Songs Using Deep Learning Model

Pawar, Rajshri (2023) A Multimodal Approach for Emotion Detection through Facial Expressions, Recommending Movies and Songs Using Deep Learning Model. Masters thesis, Dublin, National College of Ireland.

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Abstract

The term ”personality” describes a variety of traits, including emotions playing a big role, ideas, and social behaviours, that collectively give an individual their unique character. This paper explores a novel approach to Emotion detection and suggesting movies and songs according to the emotion that goes beyond traditional techniques. Through a combination of psychological, creative, and machine learning insights, our novel methodology goes into the unexplored realm of deep learning methodologies. Rather than relying on conventional techniques, we utilize a combination of transformer-based models which allows us to explore the subtle visual details that influence Emotion. Our method differs from others since we are including facial expression images and recommending movies and songs. We recognize that Emotions is a multidimensional feature of human expression, going beyond the limitations of text-based data. We use photos as a crucial data source in Emotion detection to promote originality and creativity. We aim to unlock personality features with unmatched precision by working on the facial expressions, acknowledging that words cannot truly capture the essence of a person’s emotions and personality. Our approach is a major step towards a new era in emotion detection, where a deeper understanding of human personalities may be gained through the combination of deep learning and image analysis. With the help of visual data, we can look into different sides of individuality and overstep the aspect emotion prediction with recommending the movies and songs.

Item Type:	Thesis (Masters)
Supervisors:	Name Email Hafeez, Taimur UNSPECIFIED
Subjects:	M Music and Books on Music > M Music Q Science > QA Mathematics > Electronic computers. Computer science T Technology > T Technology (General) > Information Technology > Electronic computers. Computer science B Philosophy. Psychology. Religion > Psychology > Emotions H Social Sciences > HD Industries. Land use. Labor > Specific Industries > Film Industry Q Science > Q Science (General) > Self-organizing systems. Conscious automata > Machine learning
Divisions:	School of Computing > Master of Science in Data Analytics
Depositing User:	Ciara O'Brien
Date Deposited:	20 May 2025 14:03
Last Modified:	20 May 2025 14:03
URI:	https://norma.ncirl.ie/id/eprint/7588

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