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Thesis . 2018
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Thesis . 2018
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Doctoral thesis . 2019
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Doctoral thesis . 2022
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MIRages: an account of music audio extractors, semantic description and context-awareness, in the three ages of MIR

Authors: Herrera Boyer, Perfecto;

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

Abstract

Aquesta tesi informa sobre recerca realitzada i publicada durant els últims vint anys en diferents problemes de Recuperació d'Informació Musical (MIR). Organitzem el text com a visió personal i reflexió crítica i utilitzant quatre hipotètiques edats que han configurat l'evolució del MIR. A l'edat dels extractors de característiques, presentem treballs sobre trets per a descriure sons i música, especialment timbre i aspectes tonals. A l'edat dels descriptors semàntics es treballa en la descripció de música amb conceptes d'alt nivell, com l'estat d'ànim, els instruments, les similituds, les versions musicals o els gèneres, generalment deduïts amb l'aprenentatge automàtic a partir de col·leccions anotades. En l'era dels sistemes sensibles al context, informem sobre models d'usuaris amb l’objectiu de fer recomanacions musicals i generació d'avatars, a més de factors que influeixen en les decisions d'escoltar música. S’esmenta, finalmente, una posible i més recent edat dels sistemes creatius on els descriptors, classificadors, models i metodologies d'avaluació de MIR ajuden a potenciar o ampliar la creació musical.

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.

Programa de doctorat en Tecnologies de la Informació i les Comunicacions

Country
Spain
Related Organizations
Keywords

62, Audio analysis, Music information retrieval, Music analysis, Recomanació musical, Timbre, Automatic classification of music, Semantic features, Cerca d’informació musical, Anàlisi del so, Sistemes de creació musical, https://en.wikipedia.org/wiki/Sound_and_music_computing, Descriptors semàntics, Descriptors del so, Audio features, https://en.wikipedia.org/wiki/Music_information_retrieval, Music creation systems, Music recommendation, Classificació automàtica de música

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This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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