In the seminal paper in which Alan Turing proposed his famous test for identifying intelligent machine behaviour (Turing’s test), there are already multiple speculations on whether machines can understand and do music just as humans do. Nowadays, it is undoubted that machine intelligence can expand the ways humans experience and create music. In the last decades, various communities have addressed the fundamental questions, theories, systems and practical issues around music and intelligent systems, with varying degrees of success and areas of focus: automatic composition, procedural music generation, music learning, signal and symbolic feature extraction, semantic annotation of music, emotion detection, interactive musical experience between humans and computers, and so on. However, these fields have traditionally operated, and do so still currently, through highly segmented communities, between which scarce and only sporadic and unorganized interaction occurs.
We are a community of enthusiastic academic researchers, industry practitioners and government institutions with a deep interest in strengthening all fronts of interaction between Music and Artificial Intelligence. AIM will advocate and seek for impact and outreach towards the goal of building artificial musical agents that collaborate with humans employing true musical intelligent behaviour through an organized community of practice. Thus, the goal of AIM is to connect and bring together individuals, groups, and institutions that do research and work around the different aspects of Music and AI, advocating a more cohesive Music & AI community, fostering outreach, and driving innovation in the field.
AIM is currently a DARIAH Working Group, and more community building efforts are on the works.
This is an incomplete list of topics of interest to the WG:
The WG provides the following to its participant members:
This is a list of the current AIM participants: