23 citations · 29 across the 4 of their papers we have counts for
4 papers
Proceedings of The third international workshop on eXplainable AI for the Arts (XAIxArts)
Corey Ford, Elizabeth Wilson, Shuoyang Zheng +9
This third 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…
Reducing Barriers to the Use of Marginalised Music Genres in AI
Nick Bryan-Kinns, Zijin Li
AI systems for high quality music generation typically rely on extremely large musical datasets to train the AI models. This creates barriers to generating music beyond the genres…
Exploring Variational Auto-Encoder Architectures, Configurations, and Datasets for Generative Music Explainable AI
Nick Bryan-Kinns, Bingyuan Zhang, Songyan Zhao +1
Generative AI models for music and the arts in general are increasingly complex and hard to understand. The field of eXplainable AI (XAI) seeks to make complex and opaque AI models…
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…