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Found 8 papers, 2 papers with code
Reducing Barriers to the Use of Marginalised Music Genres in AI
We undertook a 4 month international research project summarised in this paper to explore the eXplainable AI (XAI) challenges and opportunities associated with reducing barriers to using marginalised genres of music with AI models.
Proceedings of The second international workshop on eXplainable AI for the Arts (XAIxArts)
This second international workshop on explainable AI for the Arts (XAIxArts) brought together a community of researchers in HCI, Interaction Design, AI, explainable AI (XAI), and digital arts to explore the role of XAI for the Arts.
Exploring Variational Auto-Encoder Architectures, Configurations, and Datasets for Generative Music Explainable AI
This paper contributes a systematic examination of the impact that different combinations of Variational Auto-Encoder models (MeasureVAE and AdversarialVAE), configurations of latent space in the AI model (from 4 to 256 latent dimensions), and training datasets (Irish folk, Turkish folk, Classical, and pop) have on music generation performance when 2 or 4 meaningful musical attributes are imposed on the generative model.
Proceedings of The first international workshop on eXplainable AI for the Arts (XAIxArts)
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 digital arts to explore the role of XAI for the Arts.
AI (r)evolution -- where are we heading? Thoughts about the future of music and sound technologies in the era of deep learning
The students represent the future generation of AI and music researchers.
An Autoethnographic Exploration of XAI in Algorithmic Composition
The appropriation of an XAI model within an iterative workflow highlights the potential of XAI models to form part of a richer and more complex workflow than they were initially designed for.
Exploring XAI for the Arts: Explaining Latent Space in Generative Music
We increase the explainability of the model by: i) using latent space regularisation to force some specific dimensions of the latent space to map to meaningful musical attributes, ii) providing a user interface feedback loop to allow people to adjust dimensions of the latent space and observe the results of these changes in real-time, iii) providing a visualisation of the musical attributes in the latent space to help people understand and predict the effect of changes to latent space dimensions.
Extended Reality (XR) Remote Research: a Survey of Drawbacks and Opportunities
Extended Reality (XR) technology - such as virtual and augmented reality - is now widely used in Human Computer Interaction (HCI), social science and psychology experimentation.
Human-Computer Interaction
