The MIR field: From Knowledge to Data-driven, from Features to Ethical and Regulatory Considerations

Dr. Emilia Gómez / European Commission’s Joint Research Centre

Abstract: This talk 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 first focus on the paradigm shift from knowledge-driven to data-driven algorithmic design, thanks to recent developments in machine learning. After that, I will discuss the current challenges that the MIR field addresses and the current and future research challenges, notably on the social and ethical impact of MIR algorithmic systems.

Bio: 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, notably the AI Act and the Digital Services Act. She is also a guest professor in Music Technology at Universitat Pompeu Fabra in Barcelona, Spain.\n Dr Gómez has a long academic experience in the field of Music Information Retrieval, where she has contributed to different approaches for music content description, notably in pitch-content description. Starting from the music domain, she now studies the impact of AI in human behaviour, notably how AI affects jobs, decisions, fundamental rights and children. She was the first female president of ISMIR, 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 honors, e.g. EUWomen4Future, Red Cross Award to Humanitarian Technologies or ICREA Academia.",1