Title: MIRages: an account of music audio extractors, semantic description and context-awareness, in the three ages of MIR

Supervisor: Xavier Serra and Emília Gómez

Jury:  President: Geoffroy Peeters (Télécom Paris Tech); Secretary: Sergi Jordà (UPF); Vocal: Josep Lluís Arcos (IIIA - CSIC)

Abstract:

This tesis reports on research carried out and published during the last twenty years on different problems of Music Information Retrieval (MIR). We organize the text as a personal account and critical reflection along four hypothesized ages that have shaped the evolution of MIR. In the age of feature extractors, we present work on features to describe sounds and music, especially timbre and tonal aspects. In the age of semantic descriptors work on describing music with high-level concepts, such as mood, instruments, similarities, cover versions or genres, usually inferred with machine learning from annotated collections is reported. In the age of context-aware systems we report on user models for recommendation and for avatar generation, in addition to factors that influence music listening decisions. We finally discuss the possibility of a more recent age of creative systems where MIR features, classifiers, models and evaluation methodologies aid to enhance or expand music creation.

Thesis document: http://mtg.upf.edu/node/3930

video of defense: https://youtu.be/WMAjqLTSNPg