Unsupervised, 2021-22

The Machine Learning for Music (ML4M) Working Group prepares for its second series of Unsupervised events in June 2022

17 December 2021

The Machine Learning for Music (ML4M) Working Group is an interdisciplinary community of artists, scientists and engineers. Bringing together postgraduate researchers at RNCM, the University of Manchester, as well as other Manchester-based guest artists, the group is focused upon exploring the creative use of emerging Artificial Intelligence (AI) and Machine Learning (ML) technologies.

ML4M was established in 2020 by Dr Sam Salem (PRiSM Lecturer in Composition, RNCM), Professor Ricardo Climent (Professor of Interactive Music Composition, the University of Manchester), and Dr Richard Allmendinger (Associate Professor in Decision Sciences, Alliance Manchester Business School).

In June 2021, the group’s first Unsupervised event took place as part of RNCM PRiSM Future Music #3, showcasing 8 new audio-visual works created by members Anastasios Asonitis, Vicky Clarke, Hongshuo Fan, Robert Laidlow, Zakiya Leeming, Tywi Roberts, Chris Rhodes, and Ellen Sargen.

Images from the 8 new works presented at Unsupervised 2021, part of PRiSM Future Music #3

Members of our 2021-22 cohort are joined this year by Nina Whiteman, Bofan Ma, Megan Steinberg, Daniel Kidane, Jason Dominguez, Tom Baker, Melanie Wilson, Darragh Kelly, James Corely and Lirgan Yuzbegi. Our second series of events will take place in June 2022, preceded by public meetings that will offer the broader postgraduate communities of RNCM / UoM an opportunity to find out more about our work with AI and ML.

Our first Unsupervised events truly exceeded our expectations. The breadth of approaches, and the sheer creativity, of these first ML4M works is very exciting, and I look forward to seeing what our group produces for our next events in June 2022.

Dr Sam Salem, PRiSM Lecturer in Composition, RNCM

 

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