The lecture will take place in TANNA SCHULICH HALL, followed by a catered reception in the lobby of the Elizabeth Wirth Music Building. This event is free and open to the general public.
Registration
No registration is required for this event.
**CIRMMT Students wishing to have their attendance tracked for awards eligibility, please make sure to scan the QR code available at the entrance of Tanna Schulich Hall.
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Abstract
This lecture focuses on audio-based music information retrieval (MIR) and reflects on the origins of the field, the different MIR eras, and the recent developments. I will focus on the paradigm shift from knowledge-driven to data-driven algorithmic design, because of recent developments in machine learning. This paradigm shit will be presented for a representative set of well-recognized MIR tasks: pitch-content description, rhythmic description, music emotion recognition and version identification, which are linked to the concept of similarity. After that, I will discuss the current challenges that the MIR field addresses and the research trends that I foresee in the future, notably on the social and ethical impact of MIR algorithmic systems.
Biography
Dr. Emilia Gómez (MSc. Telecommunication Engineering, PhD in Computer Science, Full professor accreditation) is a senior scientist at the European Commission’s Joint Research Centre, where she leads the Human Behaviour and Machine Intelligence (HUMAINT) team that provides scientific support to EU AI policies as part of the European Centre for Algorithmic Transparency. She is also a guest professor in Music Technology at Universitat Pompeu Fabra in Barcelona, Spain.
Dr Gómez has a long academic experience in the field of Music Information Retrieval, where she researches on data-driven algorithms for music description. Starting from music, she researches the impact of AI in human behaviour, notably the impact of AI on jobs, decisions, fundamental rights and children. She was the first female president of the International Society for Music Information Retrieval, is currently a member of the OECD One AI expert group, an ELLIS (European Laboratory for Learning and Intelligent systems) fellow, and her work has been recognized by means of citations and honours, e.g. EUWomen4Future, Red Cross Award to Humanitarian Technologies or ICREA Academia.