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Research seminar by Louis Bigo on spatial representations and high level descriptors for symbolic music analysis

Research seminar by Louis Bigo on spatial representations and high level descriptors for symbolic music analysis

Monday June 17th, 2019 at 15:30h. Room 55.309 (Campus Poblenou, Universitat Pompeu Fabra)

12.06.2019

 

 

Spatial representations and high level descriptors for symbolic music analysis by Louis Bigo (Algomus team - CRIStAL laboratory, Universite de Lille)

Abstract:

This talk focus on two computational approaches to symbolic music analysis. The first approach includes the notion of pitch/chord space, that we use to reformulate in spatial terms different musical tasks as style recognition and harmonic transformations. Musical spaces are formalized with topological structures named simplicial complexes. Elementary musical objects (for example pitches or chords) are represented by simplices that are organized according to a neighborhood relationship which translates a musical property, for example consonance. Such spatial formulation of musical structures enables the application of geometrical and topological operations, such as translations, rotations, embeddings and filtrations, that bring original approaches to music composition and analysis.
The second approach focus on the extraction of high level musicological features that can serve automated analysis of classical forms. We will discuss the detection of cadences and the retrieval of section boundaries in sonata form with different machine learning methods.

Biography:

I am associate professor (maître de conférence) in computational musicology at University of Lille in the Algomus team (Algorithmic musicology) at CRIStAL laboratory since 2016. My research interests include mathematical models and machine learning for automatic music generation, analysis and classification. I received my Ph.D in Computer Science on the topic of symbolic music representations and spatial computing in 2013 at IRCAM (French Institute for Research and Coordination in Acoustics/Music) and LACL, University Paris 12. I joined the European project Learning To Create on music and machine learning from 2014 to 2016 in the Music Informatics Group at the University of Basque Country in San Sebastian, Spain.

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Louise Bigo

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