Tonality Estimation in Electronic Dance Music a Computational and Musically Informed Examination
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Tonality Estimation in Electronic Dance Music A Computational and Musically Informed Examination Ángel Faraldo Pérez TESI DOCTORAL UPF / 2017 Thesis Directors: Dr. Sergi Jordà Puig Music Technology Group Department of Information and Communication Technologies Universitat Pompeu Fabra, Barcelona, Spain Dissertation submitted to the Department of Information and Communication Tech- nologies of Universitat Pompeu Fabra in partial fulfilment of the requirements for the degree of DOCTOR PER LA UNIVERSITAT POMPEU FABRA Copyright c 2017 by Ángel Faraldo Licensed under Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 Music Technology Group (http://mtg.upf.edu), Department of Information and Communication Tech- nologies (http://www.upf.edu/dtic), Universitat Pompeu Fabra (http://www.upf.edu), Barcelona, Spain. The doctoral defence was held on ......................... at the Universitat Pompeu Fabra and scored as ........................................................... Dr. Sergi Jordà Puig (Thesis Supervisor) Universitat Pompeu Fabra (UPF), Barcelona, Spain Dr. Agustín Martorell Domínguez (Thesis Committee Member) Universitat Pompeu Fabra (UPF), Barcelona, Spain Dr. Gianni Ginesi (Thesis Committee Member) Escola Superior de Musica de Catalunya (ESMUC), Barcelona, Spain Dr. Anja Volk (Thesis Committee Member) Universiteit Utrecht, The Netherlands This thesis has been carried out at the Music Technology Group (MTG) of Universitat Pompeu Fabra in Barcelona, Spain, from January 2014 to November 2017, supervised by Dr. Sergi Jordà Puig and Prof. Perfecto Herrera Boyer. My work has been supported by the Department of Information and Communication Technologies (DTIC) PhD fellowship (2015-17), Universitat Pompeu Fabra, and the European Research Council under the European Union’s 7th Framework Program, as part of the GiantSteps project (FP7-ICT-2013-10, grant agreement 610591). Efforts in several parts of this thesis were closely related to the GiantSteps project and have been carried out in collaboration with the partner institutions (Johannes Kepler University, Linz; Native Instruments, Berlin; Reactable Systems, Barcelona; Studio for Electro-Instrumental Music, Amsterdam), and with the Music and Multimodal Interaction Lab at the MTG, lead by Dr. Sergi Jordà. My closest collaborators inclu- de (alphabetically ordered) Pere Calopa, Daniel Gómez-Marín, Peter Knees, Martin Hermant and Cárthach Ó Nuanáin. Abstract This dissertation revolves around the task of computational key estimation in elec- tronic dance music, upon which we perform three interrelated operations. First, we attempt to detect possible misconceptions within the task, which is typically accom- plished with a tonal vocabulary overly centred in Western classical tonality, reduced to a binary major-minor model which might not accomodate popular music styles. Se- cond, we present a study of tonal practises in electronic dance music, developed hand in hand with the curation of a corpus of over 2,000 audio excerpts, including multiple subgenres and degrees of complexity. Based on this corpus, we propose the creation of more open-ended key labels, accounting for other modal practises and ambivalent tonal configurations. Last, we describe our own key finding methods, adapting exis- ting models to the musical idiosyncrasies and tonal distributions of electronic dance music, with new statistical key profiles derived from the newly created corpus. VII Resum Aquesta tesi doctoral versa sobre anàlisi computacional de tonalitat en música elec- trònica de ball. El nostre estudi es concentra en tres operacions fonamentals. Primer, intentem assenyalar possibles equívocs dins de la pròpia tasca, que normalment es desenvolupa sobre un vocabulari tonal extremadament centrat en el llenguatge de la música clàssica europea, reduït a un model binari major-menor que podria no acomo- dar fàcilment estils de música popular. Seguidament, presentem un estudi de pràcti- ques tonals en música electrònica de ball, efectuat en paral lel a la recol lecció i anàlisi · · d’un corpus de més de 2.000 fragments de música electrònica, incloent diversos sub- gèneres i graus de complexitat tonal. Basat en aquest corpus, suggerim la creació d’etiquetes tonals més obertes, que incloguin pràctiques modals així com configura- cions tonals ambigües. Finalment, descrivim el nostre sistema d’extracció automàtica de tonalitat, adaptant models existents a les particularitats de la música electrònica de ball, amb la creació de distribucions tonals específiques a partir d’anàlisis estadísti- ques del recentment creat corpus. IX Resumen Esta tesis doctoral versa sobre análisis computacional de tonalidad en música electró- nica de baile. Nuestro estudio se concentra en tres operaciones fundamentales. Prime- ro, intentamos señalar posibles equívocos dentro de la propia tarea, que normalmente se desarrolla sobre un vocabulario tonal extremadamente centrado en el lenguaje de la música clásica europea, reducido a un modelo binario mayor-menor que podría no acomodar fácilmente estilos de música popular. Seguidamente, presentamos un es- tudio de prácticas tonales en música electrónica de baile, efectuado en paralelo a la recolección y análisis de un corpus de más de 2.000 fragmentos de música electró- nica, incluyendo varios subgéneros y grados de complejidad tonal. Basado en dicho corpus, sugerimos la creación de etiquetas tonales más abiertas, que incluyan prác- ticas modales así como configuraciones tonales ambiguas. Por último, describimos nuestro sistema de extracción automática de tonalidad, adaptando modelos existentes a las particularidades de la música electrónica de baile, con la creación de distribucio- nes tonales específicas a partir de análisis estadísticos del recién creado corpus. XI la vida es la memoria y el hombre es el azar Fernando Arrabal Acknowledgements Let me begin this acknowledgement with my loved ones. Without them, I would not even consider embarking in this journey. Padre and Madre, thanks for supporting me so instinctively, and for making me embrace the doubt. Marta, the most intense supporter, the greatest lover, the worst cook, partner of so many new things. I would have died from starvation and sadness if you weren’t around me during these last months. Thank you for being, simply, as you are. Yolanda, we moved from the Dark places into the Bright, together, and that was the very beginning of my whole PhD adventure. Then, our souls decided to find out about the world separately. Today, I arrive at the end of what brought us here, and I thank you for all your support and understanding. Silvia, Emilio, you are the true friends everyone deserves. I am so lucky to have you around, and it is probably because of you that I haven’t gone completely mad during my writing. You also introduced me to so many new souls, to Xiana, the people of Can Masdeu, the good Sun-days in Barcelona. Cárthach, Martinuqui, Dani, you were the best imaginable companions for such a journey. We shared everything. Drugs, doubts, study. We shaped our projects together so they could complement each other. We tried. Most of the times we failed. But the few things we achieved, we did greatly together. You were the most gorgeous occupants of the MTG, that place that was our home for around four years, and where we met other amazing fellows. Juanjo, Marius, the GiantSteps project and the people involved in it, Peter Knees, the two Mickael’s, Kristina. Bucci, the great Bucci. It was so good to shape my project through the various cities, beers and conversations. Thank you for that. Parts of my research would not have been even imagined without three years of quite intensive teaching, with a number of students testing prototypes enthusiastically and providing such helpful insights. I’ve learnt a lot from that process. Eduard Mas, Ser- gio Latre, your help annotating and correcting almost 1,500 audio tracks of electronic dance music is priceless, as much as it is the exceptional work of Daniel G. Camhi analysing with careful detail a corpus of 500 additional fragments. Your contribu- tions have been so important, that a whole chapter of this dissertation is written in your honour. I am almost about to put an end to a process that has taken four years of my life. And I haven’t mentioned the two beings thanks to whom this has been possible. Thank you, Perfe. You have been the greatest scientific supervisor I have ever met. Your patience XV XVI ACKNOWLEDGEMENTS deserves a monument, your knowledge a library. Your capacity to release tension and give support with small actions, is inestimable. Sergi, the genius in disguise. We met briefly on Skype, and that was enough to make up my mind and come to Barcelona, leaving eight Dutch years behind. You have been an excellent boss, advisor, an ex- tremely balanced Yin complementing Perfe’s Yang. A trip companion, and after these years, a friend. Thank you so very much for trusting. Barcelona, 13th December, 2017 Ángel Faraldo Table of Contents Abstract VII Resum IX Resumen XI Acknowledgements XV Table of Contents XVII List of Figures XXI List of Tables XXV 1 Introduction1 1.1 Motivation................................ 2 1.2 Contexts of Action ........................... 3 1.2.1 Electronic, Dance, Music.................... 3 1.2.2 Music, Information, Retrieval ................. 8 1.3 Research Objectives........................... 10 1.4 Actions in Context ........................... 12 1.4.1 A Study of Tonal Practices in EDM . 12 1.4.2 Algorithms for Key Estimation in EDM . 13 1.5 Structure of this