Junhyung So, Dongwook Kim, John Park

Music Tinder

We attempted to create a program that recommends the user music from our database. The program starts with a questionnaire that will try to determine the mood/personality of the user and give music suggestions based on the results. Our database contains three different types of music: classical/contemporary composers, 1950s-2000, and 2000s-present. Each type has five groups of songs based on the mood: dark, joyful, sorrowful, energetic, and calm. For example, if the user selects classical music and tests for a dark mood, then the program will recommend them Beethoven’s Moonlight Sonata and additional suggestions depending on the user’s desire. Because classical music is not as well-listened to as before, we wanted to use this program to recommend users to listen to more classical music and introduce less known composers. We also included music from the 1950s-2000 because users can listen to the old pop songs and see how different it was to present day pop music. We couldn’t leave out songs from the present because some users might not want to listen to classical or old pop music. We categorized songs based on mood because songs can be a stress reliever to help the users mentally. This program is useful when the user doesn’t know what new music to listen to and wants a change from their regular playlists.

Unlike Spotify, our questionnaire can help the user know how they truly feel and can easily direct them to the songs we have. We can improve this program by adding a music player, an option to create playlists, and waveforms to match the song. We would also make this into a website because Python is limited for the ideas we wanted to do. We would change the questions each time the quiz is completed in order accurately determine the user’s mood.

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