The goal of this project is to leverage the rich content of song lyrics to connect each song with relatable concepts such as moods, occasions, and themes. A direct application of this automatic tagging system would be to produce playlists associated with different emotions or serve specific purposes (after break-up songs, holiday music, party mix, et cetera). An initial target for final product would be a collection of moods and topics that a user can select to retrieve an associated list of songs. A more advanced version would allow the user to type in a specific emotion or adjective and listen to a list of related songs. The ultimate goal is to help create an interactive and highly personalized music experience for the users.
If time permits, we might be able to extend the project further in either modeling or research directions. A modeling enhancement would be to not only process lyrics but also take into consideration other characteristics of songs such as genre, vintage, writer, singer, et cetera, when making connections between them. A research potential of interest, on the other hand, would be to analyze and/or visualize lyrical themes across time. Overall, depending on the data accessibility and quality, we see many potentials in this project and aim to explore various options along the way with the end goal of producing personalized music experience for users in mind.
Check out the project demo website here.