Transforming data

In learning to understand data in a more theoretical perspective through a data visualization class in my graduate program, I wanted to explore ways in which elements of a song like tempo, dynamics, rhythm, etc, can be interpreted as data points. Music and sound naturally lends itself to visualization and codification, especially due to its repetitive nature, with sheet music being the most basic and widely used form of musical notation. In this project, I learned p5.js (p5.sound Library in particular) to create a more complex audio reactive visual.

My original idea was to use the p5 sound library to analyze the frequency and amplitude, using the p5.FFT and p5.Amplitude functions. However, with the timeline of the project being 3 weeks for my Transforming Data class, I was unable to fully grasp the frequency analysis function. As a result, I got separated sound files of a song and analyzed a selection of sound files’ amplitudes, mapping the changes in amplitudes to circle diameters and line lengths.