The focus of the Audio Signal Processing Lab of the MTG is to advance in the understanding of sound and music signals by combining signal processing and machine learning methods with semantic technologies. We work both on data-driven methodologies, in which the development and use of large data collections is a fundamental aspect, and on knowledge-driven approaches, in which domain knowledge of the problem to be addressed is needed. Combining these research approaches, we are able to tackle practical problems related to music exploration and recommendation, classification of sounds, and music performance evaluation for music education.

Team

Xavier Serra, Faculty, Head of lab Eduardo Fonseca, PhD student
Bariş Bozkurt, collaborator Minz WonPhD student
Dmitry Bogdanov, Postdoc Alastair Porter, Researcher
Frederic Font, Postdoc     Andrés Ferraro, Researcher
Rafael Caro RepettoPhD student  Błażej KotowskiResearcher
Rong GongPhD student Pablo Alonso, Researcher
Jordi Pons PhD student  Albin Correya, Researcher
Xavier FavoryPhD student Vsevolod Eremenko, Researcher
António Ramires, PhD student Philip Tovstogan, PhD student

Research