Date: Wednesday, April 25th, 2018 at 11:00h in room 55.309 (Tanger Building, UPF Communication Campus)

Title: Similarity and Style in Electronic Dance Music Drum Rhythms

Supervisor: Dr. Sergi Jordà

Jury:  President: Dr. Matthew Davies (INESC TEC), Secretary: Dr. Dmitry Bogdanov (UPF), Vocal: Dr. Jason Hockman (SCDT, Birmingham City Univ.).

Abstract:

This thesis presents original research carried out in the topic of electronic dance music (EDM) drum sequencing, a fundamental and yet underdeveloped subject in the music production literature. The work undertaken is focused in two main areas: similarity between drum patterns and modelling of drumming style. The study of pattern similarity is rooted in current knowledge on human processing of monophonic rhythms, and is expanded until a model capable of predicting similarity sensations of polyphonic drum rhythms is reached. With this model, RhythmSpace, a graphical system for the continuous real-time exploration of drum pattern collections, is developed. The second area of research, drumming style modelling, is approached from a statistical perspective, developing a generative model capable of learning styles from examples and creating original drum patterns in the learned styles. This model allows high-level musical flexibility, letting a musician combine and transform styles in real-time during the generative process. Taking advantage of this model, a style-based drum machine application, DrDrums, is implemented and evaluated in subject-based experiments.

Thesis document: http://mtg.upf.edu/node/3932