Wyatt Bier
University of Dayton
Srujan Reddy Bollampally
University of Dayton
Ngô Quang Hải
Ben Holdcraft
University of Dayton
Thomas McGinley
The Music Mood Classifier is a cloud-based intelligent system that analyzes music input and returns a mood profile for that song. Users can enter song lyrics, a song title, or both, and the system will classify the mood and suggest activities the song is suited for. The system consists of a backend REST API and a simple frontend interface where users interact with the service.
Music is closely tied to how people feel and what they are doing day to day, but most tools for discovering Music focuses on genre rather than mood. This project aims to build a simple and fun tool that classifies a song's emotional mood and suggests activities that pair well with it, like studying, working out, or relaxing. The scope includes building the backend microservice, connecting it to a frontend, and deploying the full system to the cloud.