Machine-learning music project UNSUPERVISED 2021 shortlisted for Digital City Award

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A University of Manchester machine-learning music project has been shortlisted for a Prolific North Digital City Award.

UNSUPERVISED 2021 is a product of the ML4M (Machine Learning for Music) working group, a collaboration between the Royal Northern College of Music’s Centre for Practice and Research in Science and Music (PRiSM), the University’s NOVARS research centre and the Alliance Manchester Business School.

The fledgling ML4M group fuses postgraduate composers, artists and specialists in computer science and engineering.

UNSUPERVISED 2021 is ML4M’s debut project and features eight new works engaging with machine learning technology. It has been created by eight RNCM PRiSM and University of Manchester doctoral researchers and artists. Five of these pieces were created using PRiSM’s flagship software tool PRiSM SampleRNN and were as a result of collaborations between students and Dr Christopher Melen, PRiSM Research Software Engineer.

“Being a part of the UNSUPERVISED team since its inception has been an incredible and rewarding experience,” said Dr Chris Rhodes, Doctoral Researcher, NOVARS Centre, University of Manchester. “Working in a collective, focused on the application of AI for musical creativity, is always inspiring. As curious members, we help each other think about how AI can be applied to music composition by describing our philosophy when applying AI to art, our methods (technical and aesthetic) and our artistic angles.”

UNSUPERVISED 2021 has been shortlisted for the Digital City Award Best Use of Technology - Not-for-profit category. The Awards celebrate the organisations and individuals who are working to build a better future through technology.

The awards ceremony will take place on 10 March 2022 at the Etihad Stadium, where singer Sheila Gordhan will present the winners.

“We are delighted to have been nominated for the Digital City Awards,” said Dr Sam Salem, RNCM PRiSM Lecturer, who established ML4M in 2020 with Professor of Interactive Music Composition at The University of Manchester Ricardo Climent and Dr Richard Allmendinger, Associate Professor in Decision Sciences at AMBS.

“The Machine Learning for Music Working Group is still very much in its infancy … and it is therefore hugely encouraging to receive this nomination for our first event,” Dr Salem added. “We look forward to presenting our latest work in the next UNSUPERVISED events, scheduled for June 2022.”

The shortlist for this year’s Digital City Awards can be found here.