Emilia Gómez is an Associate Professor (Serra-Húnter Fellow) at the Department of Information and Communication Technologies, Universitat Pompeu Fabra, Barcelona, where she leads the Music Information Research Lab at the Music Technology Group. She graduated as a Telecommunication Engineer at Universidad de Sevilla (1999) and studied piano performance at Seville Conservatoire of Music. She then received a DEA in Acoustics, Signal Processing and Computer Science applied to Music at IRCAM, Paris (2000) and a PhD in Computer Science at the UPF (2006, awarded by EPSON foundation). She has been lecturer at the Escola Superior de Música de Catalunya and visiting researcher at the Royal Institute of Technology, Stockholm (Marie Curie Fellow), McGill University, Montreal, and Queen Mary University of London. She has co-authored more than a 100 peer-reviewed publications and software libraries, and contributed to more than 20 projects, mostly funded by the European Commission.

Research interests

Her research is motivated by her background in both engineering and music and is within the Music Information Retrieval (MIR) field. She tries to understand the way humans describe music and emulate these descriptions by computational models dealing with big music data. By integrating knowledge from signal processing, music theory, cognition and machine learning, she has developed methods to automatically describe music data (audio signals, scores and visual information) in terms of melody, tonality and rhythm; to measure similarity between pieces and automatically classify music according to style, emotion or culture. She is currently president-elect of the International Society for Music Information Retrieval and co-editor in chief of the open access journal Transactions of ISMIR.

Keywords

Music information retrieval, big data, machine learning, audio signal processing