Classification of Ballroom Dancing Music Using Machine Learning
by Noemie Voss and Phong Nguyen
Abstract – Ballroom dancing is a set of partner dances enjoyed both socially and competitively around the world. There are 10 different types of ballroom dancing, each danced to different styles of music. However, there are currently no algorithms to help differentiate and classify pieces of music into their individual dance types. This makes it difficult for beginner and amateur ballroom dancers to distinguish pieces of music and know which type of dance corresponds to the music they are listening to. We have created a machine learning classification model, which, by learning from known examples, is able to classify which dance type pieces of music correspond to. The final accuracy of this model is 89%. With this model, beginners to ballroom dancing will have an easier method of searching for and distinguishing between specific types of ballroom dancing music. This can also help people socialise and enjoy their time dancing with a partner.