Publication Date
Spring 2026
Degree Type
Master's Project
Degree Name
Master of Science in Computer Science (MSCS)
Department
Computer Science
First Advisor
Navrati Saxena
Second Advisor
Sayma Akter
Third Advisor
Mihir Dhirajlal Satra
Keywords
Emotion-Based Music Recommendation, Deep Learning, Facial Emotion Recognition, Music Mood Classification, XGBoost, Spotify Audio Features.
Abstract
Music forms an important part of human existence and has significant impacts on the emotions of humans; however, due to the presence of abundant digitized music, it becomes very difficult for the user to select music that suits his/her emotion at that instant of time. In this research project, we have designed an Emotion-Based Music Recommendation System that makes use of ideas from face recognition and music mood to recommend suitable music to the user depending upon the emotions experienced by him/her. This emotion detection system works using a webcam to capture the facial expressions of the user and using Deep Learning technology for emotion recognition.
Recommended Citation
Kanamathareddy, Harshini, "Emotion-Based Music Recommendation System" (2026). Master's Projects. 1789.
DOI: https://doi.org/10.31979/etd.6q7k-t4fs
https://scholarworks.sjsu.edu/etd_projects/1789
