Back Research seminar by Martín Rocamora on the analysis of Uruguayan candombe drumming

Research seminar by Martín Rocamora on the analysis of Uruguayan candombe drumming

Tuesday September 6th, 2022 at 15h in room 55.410 (Universitat Pompeu Fabra)
29.08.2022

Imatge inicial

Title:

Musical traits and performance practice of Uruguayan candombe drumming: an approach from computational musicology

Abstract:

Uruguayan candombe drumming is a rich musical practice deeply rooted in the Afro-Atlantic tradition. Although not very well-known abroad, Uruguayan candombe possesses considerable rhythmic wealth and deserves wider recognition. In acknowledgment of its rich history and cultural value, in 2009, it was inscribed on the Representative List of the Intangible Cultural Heritage of Humanity by UNESCO. This talk aims to describe the most characteristic performance practices of candombe drumming and analyze its most relevant musical traits, with particular attention to the rhythmic patterns of the three drums used in candombe and their interplay. The talk also will give an overview of the research we have been conducting over the last few years on computational rhythm analysis from audio recordings, considering Uruguayan candombe drumming as a case study. It comprises the creation of datasets, the discovery and analysis of rhythmic patterns, the study of micro-timing, and the development of algorithms for beat and downbeat tracking. Finally, it also discusses our recent efforts to improve and extend the methods to other music traditions, particularly Brazilian Samba.

Bio:

Martín Rocamora is currently an Assistant Professor (full-time) in Signal Processing at Universidad de la República (UDELAR), Uruguay. He holds B.Sc, M.Sc., and D.Sc. degrees in Electrical Engineering from the School of Engineering, UDELAR. He was a Teaching Assistant in Music Technology at the School of Music, UDELAR. His research focuses on applying machine learning and signal processing to audio signals, with applications in machine listening, music information retrieval, and computational musicology.

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