Artificial Intelligence in Music and Performance: A Subjective Art-Research Inquiry
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This article presents a five-year collaboration situated at the intersection of Art practice and Scientific research in Human-Computer Interaction (HCI). At the core of our collaborative work is a hybrid, Art and Science methodology that combines computational learning technology – Machine Learning (ML) and Artificial Intelligence (AI) – with interactive music performance and choreography. This article first exposes our thoughts on combining art, science, movement and sound research. We then describe two of our artistic works Corpus Nil and Humane Methods – created five years apart from each other – that crystallize our collaborative research process. We present the scientific and artistic motivations, framed through our research interests and cultural environment of the time. We conclude by reflecting on the methodology we developed during the collaboration and on the conceptual shift of computational learning technologies, from ML to AI, and its impact on Music performance.
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