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A Mobile Application for Creating Dance Choreography according to Musicality of Inputted Audio using Machine Learning

Authors

Keren Brown1 and David Wei2, 1USA and2California State Polytechnic University, USA

Abstract

Even the best writers in history were not blessed enough to have a constant surge of inspiration, a never-endingflowof ink on paper, or fingers flying across keyboards. These blocks in creativity are commonly known as writer's block, and many people experience this, since communication is important in every subject. Less commonly knownisdancer's block, which is when a choreographer experiences a stop in inspiration while choreographing [1]. Theseblocks can continue for days or even weeks, before an idea strikes the dancer, setting back the ef iciency of choreographing. When due dates come into play, such as choreographing for a production, show, or assignment, adancer cannot put forth their best choreography, and will be left feeling unsatisfied with the quality of their work. When a choreographer faces a challenge towards creating original choreography, how can one gain inspirationtoovercome this block [2]? How can we ensure that the inspiration given is appropriate for the song and style whichthe choreographer is designing the dance to? This paper develops an application to choreograph visuals inacreative manner, while assessing the musicality of the audio in order to reflect the same emotion in the movement. We applied our application to a jazz piece to be performed as part of a local high school dance show and conducteda qualitative evaluation of the approach. The results show that with the software application, dancers will be abletofind inspiration to continue choreographing, pushing them past a barrier of creativity, and allowing themto finishtheir dance with a quality of choreography that they can be proud to present [3].

Keywords

Dance, Choreography, Machine Learning, Audio Analysis