UnSupervised NEWS
Responses to the Digital City Award Nomination by the UnSupervised Group
“My compositional process sees me working in all kinds of collaborations with performers to create new pieces, often creating a space to learn from each other and reflect this in our work. In this project, the ML4M group became an extended community of collaborators for me, a rich resource in which to share knowledge, ideas and reflect on AI behaviours. I look forward to seeing how these relationships will develop in future pieces.”
— Ellen Sargen, RNCM PRiSM Doctoral Researcher
“Working alongside such a talented and diverse group of artists and specialists; comparing notes over a whole academic year; sharing each other’s successes and failure during experimentation; and seeing the final works come together has been one of the highlights of my PhD programme. The support from PRiSM for working with sampleRNN was just one of the aspects which opened up whole new creative avenues for me.”
— Tywi Roberts, RNCM PRiSM Doctoral Researcher
Don’t worry about sounding professional. Sound like you. There are over 1.5 billion websites out there, but your story is what’s going to separate this one from the rest. If you read the words back and don’t hear your own voice in your head, tha“Unsupervised was a great opportunity to discover what ML can offer a creative practice, and working with the ML4M group has been a wonderful way to explore this new technology as a community.”
— Zakiya Leeming, RNCM PRiSM Doctoral Researchert’s a good sign you still have more work to do.
“We are delighted to have been nominated for the Digital City Awards. 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. We look forward to presenting our latest work in the next UNSUPERVISED events, scheduled for June 2022.”
— Dr Sam Salem, RNCM PRiSM Lecturer
“The success of ‘Unsupervised’ is based on the fact that the composers involved come from different backgrounds and yet we all attempt to understand this new technology in musical and philosophical terms.”
— Anastasios Asonitis, Doctoral Researcher, NOVARS Research Centre, the University of Manchester
“Being a part of the UNSUPERVISED team since its inception has been an incredible and rewarding experience. 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.”
— Chris Rhodes, Doctoral Researcher, NOVARS Centre, University of Manchester
Internal event: What can AI do for Arts, Culture & Creativity Research at UoM?
Date: Wednesday 15th December 2021
Time: 15:00 – 16:30 Register here
PROGRAMME
• Welcome and Context
Dr Kostas Arvanitis, Digital Futures Creative and Heritage Lead
• AI Trends, Directions and UoM Strengths
Professor Sophia Ananiadou, Deputy Director, Institute for Data Science and Artificial Intelligence
• Modelling User Engagement with Interactive Media
Jonathan Carlton, PhD student, School of Computer Science
• Discovering Novel Pathways through Collections: A Museum Recommender System
Lukas Noehrer, PhD student and Co-Organiser of the Alan Turing Institute AI&Arts Group
• Using computational linguistics to detect markers of Parkinson's disease in typing data
Dr Colin Bannard, Senior Lecturer in Linguistics
• AI use in creativity and communities
Dr Anita Greenhill, Senior Lecturer, AMBS
Dr Joe Ravetz, Future-Proof Cities Lead for Manchester Urban Institute
• Experimenting with AI in the Library
Ian Gifford, Head of Digital Development, John Rylands Library
• Sad Dog Eating: Composition strategies, hybridisation and distributed creativity with Machine Learning `
Zakiya Leeming, Doctoral Composer at the Centre for Practice and Research in Science and Music (PRiSM), Royal Northern College of Music (RNCM) • UNSUPERVISED ML4M Group
• Classifying Biometric Data for Novel Musical Expression within Composition
Chris Rhodes, PhD Candidate in Music Composition at NOVARS Research Centre • UNSUPERVISED ML4M Group
• AURA MACHINE: Machine Learning & Musique Concrete
Vicky Clarke, Artist in Residence at NOVARS, European Art-Science-Technology Network for Digital Creativity• UNSUPERVISED ML4M Group