most citedExploring XAI for the Arts: Explaining Latent Space in Generative Music

10 citations · 14 across the 5 of their papers we have counts for

collaborators

5 papers

cs.HC2023

A Guide to Evaluating the Experience of Media and Arts Technology

Nick Bryan-Kinns, Courtney N. Reed

Evaluation is essential to understanding the value that digital creativity brings to people's experience, for example in terms of their enjoyment, creativity, and engagement. There…

cs.AI20233 cited

Proceedings of The first international workshop on eXplainable AI for the Arts (XAIxArts)

Nick Bryan-Kinns, Corey Ford, Alan Chamberlain +6

This first international workshop on explainable AI for the Arts (XAIxArts) brought together a community of researchers in HCI, Interaction Design, AI, explainable AI (XAI), and di…

cs.CY2023

AI (r)evolution -- where are we heading? Thoughts about the future of music and sound technologies in the era of deep learning

Giovanni Bindi, Nils Demerlé, Rodrigo Diaz +18

Artificial Intelligence (AI) technologies such as deep learning are evolving very quickly bringing many changes to our everyday lives. To explore the future impact and potential of…

cs.SD20231 cited

An Autoethnographic Exploration of XAI in Algorithmic Composition

Ashley Noel-Hirst, Nick Bryan-Kinns

Machine Learning models are capable of generating complex music across a range of genres from folk to classical music. However, current generative music AI models are typically dif…

cs.AI202310 cited

Exploring XAI for the Arts: Explaining Latent Space in Generative Music

Nick Bryan-Kinns, Berker Banar, Corey Ford +4

Explainable AI has the potential to support more interactive and fluid co-creative AI systems which can creatively collaborate with people. To do this, creative AI models need to b…