Music Information Retrieval and its Application in Music Recommender Systems

Music Information Retrieval (MIR) is an interdisciplinary field concerned with the extraction of information from music and its analysis. Starting to be acknowledged as a scientific field at the beginning of this century, today many of its applications have been transformed in world widespread technologies: from recommender systems helping us in finding music in streaming services, to automatic genre and mood recognition systems that generate tailored music playlists. In this talk, I will start by presenting the history and evolution of MIR as a field, then focusing on one of its most successful applications, music recommender systems. 

Lorenzo Porcaro is a research scientist at the European Center of Algorithmic transparency (ECAT), part of the European Commission's Joint Research Centre. His work focus on assessing the impact that recommender systems have on their users, with a focus on human rights violation and discrimination. He holds a PhD in Information and Communication Technology, and Master's degrees in Sound and Music Computing (M.Sc.) and Intelligent Interactive Systems (M.Sc.) from Universitat Pompeu Fabra (Spain). His research interests include recommender systems, social computing, human-computer interaction, and music information retrieval.

University of Glasgow Information Retrieval (IR) Group