Inspiration
Anushka and I bonded over music, so we decided to create something that would make listening together an even better experience.
What it does
This project allows music listeners to choose a mood for the time being. The project uses the frequencies of each chord to plot a waveform that resembles a chord progression. The chord progression that is present most frequently and the area of Thayer's 2D Emotion model it occupies (which is measured by variance and energy) determines the overall mood of the song. If the listener has never heard the song before, this project determines whether it corresponds to the mood they are in or not.
How we built it
We built it using API from Spotify and Thayer's 2D Emotion model.
Challenges we ran into
We were struggling to figure out how to categorize specific chord progressions into moods.
Accomplishments that we're proud of
We are proud to have applied our beginner-level Python knowledge for the first time, related to a sector that we want to venture into.
What we learned
We learned how to utilize an existing API - we realized that the process of tweaking or creating our own API is time-consuming. So, we made use of the data already available.
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