/Topological-Descriptors-for-Symbolic-Music-Genre-Classification

During the period of November 2019 and August 2020 I carried out my internship atT ́el ́ecom Paris in Paris. I worked under the Supervision of Isabelle Block as part of theImages team. We overtook the endeavour of automated musical analysis for musical genreclassification. The goal was to refine the notion of harmonic trajectory descriptor andinvestigate how to improve classification on symbolic music data. The hypothesis is thatthe harmonic trajectory of musical piece is an imprint that defines the genre of the pieceat a certain level.In this work, we focus on different methods to utilize the harmonic trajectory descriptoreither for classification purposes or transcription and key estimation purposes. We workedwith large databases of symbolic music scores, such as the Lakh Data-set. We presented amodular, in regards to descriptors, system for supervised learning, mainly using supportvector machines.

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