College
College of Engineering and Polymer Science
Date of Last Revision
2026-04-28 12:31:29
Major
Computer Science
Honors Course
CPSC 497 - Indiv Study: Computer Science
Number of Credits
3
Degree Name
Bachelor of Science in Computer Science
Date of Expected Graduation
Fall 2026
Abstract
The Music Mood Analyzer Dashboard identifies and visualizes the emotional tone of songs using audio features like tempo, energy, and valence. It classifies tracks into moods such as happy, sad, or calm and presents insights through an interactive dashboard. The project combines music analysis and data visualization to help users understand how sound relates to emotion.
Research Sponsor
Zhong-Hui Duan
First Reader
En Cheng
Second Reader
Yingcai Xiao
Honors Faculty Advisor
Zhong-Hui Duan
Proprietary and/or Confidential Information
No
Community Engaged Scholarship
No
Recommended Citation
Bhattarai, Biswash, "AI-Based Music Mood Analysis with Historical and Real-Time Data" (2026). Williams Honors College, Honors Research Projects. 2105.
https://ideaexchange.uakron.edu/honors_research_projects/2105
Comments
This project presents an end-to-end AI-based system designed to bridge the gap between music streaming and emotional context. By integrating a DistilBERT-powered sentiment analysis model with real-time data from the Spotify and Genius APIs, the system offers dynamic, mood-based recommendations. The implementation features a full-stack architecture using FastAPI and a modular frontend to demonstrate the practical application of Natural Language Processing (NLP) in enhancing user well-being through personalized music discovery.