Project

In our project we use Artificial Intelligence applied to real-time audio analysis to create new tools to support musical practice and bring a new quantitative approach to artistic research.

Carl Czerny     –      In the past months we have been experimenting with the musical examples that Carl Czerny proposes in his treatise on interpretation (op. 500). This work is an essential piece for the study of musical performance in the Classical and Romantic period. Czerny was an outstanding figure and, as a pupil of Beethoven and teacher of Liszt, he conveys in his interpretative vision the characteristics of the transition between two periods. Our experiments are carried out on a fortepiano of the period.

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Team

Eulàlia Febrer holds a PhD in Popular Music from Cardiff University, a Master’s degree in Music as an interdisciplinary art from the UB and a degree in Musicology from the ESMUC. She combines her teaching and research work at CSIB, the International University of La Rioja and the Centre for Image and Multimedia Technology (UPC). Eulàlia is currently the coordinator of the Musicological Research Group of Menorca (Institut Menorquí d’Estudis). https://www.researchgate.net/profile/Eulalia-Febrer-Coll

Andrés Fernández is a musician and PhD student in Machine Learning at the Max Planck Institute for Intelligent Systems (University of Tübingen). He previously worked on the “AI for Sound” project (University of Surrey). He holds a degree in computer science (Goethe University) and a diploma in composition (HfMDK Frankfurt). https://aferro.dynu.net

Joan Travé is a pianist, fortepianist and researcher. He graduated with honours from the CSIB (professors Miquel Estelrich and Manuel Carra). He holds two master’s degrees (performance and piano pedagogy with Prof. Catherine Vickers) from the HfMDK Frankfurt. He has studied fortepiano with Prof. Jesper Christensen and physiology of piano technique with Laurent Boullet. https://joantrave.net/en