Student papers at NIME and AI Music Studies
Lab papers accepted at NIME 2024 and at the First International Conference in AI Music Studies.
Occupational Therapy Methods in the Design of Accessible Musical Instruments
Andrew McMillan, Fabio Morreale
To be presented at NIME 2024, Utrecht, The Netherlands
This study explores the integration of Occupational Therapy techniques within the evaluation of movement and functionality concerning users of Accessible Musical Instruments (AMI). It examines the current application of these techniques in design methodologies and contemplates their potential adaptation and incorporation into AMI design. The paper presents findings derived from a conventional occupational therapy approach alongside two inquiries that modify and expand upon this approach through the integration of sensor technologies. The outcomes of two tasks, each employing sensor technology to gauge and appraise movement and functionality, are presented. These findings are to illustrate how designers can integrate methodologies pertaining to the analysis of a range of movement and functionality within their design frameworks.
Accessing Musical Creativity:Embedded Ideologies in Generative-AI Music Tools
Liam Pram, Fabio Morreale
To be presented at the First International Conference in AI Music Studies, Stockholm, Sweden
The accessibility of musical creativity to all people is one of the potential use cases of Generative-AI, and an ideological position which could be exploited for profit. Sturm and colleagues (2024) found accessibility a common subject in the literature on creativity in AI, and central to the scalability required to make AI Music tools profitable in the commercial sector. The pursuit of accessibility casts musicianship as a barrier to entry for musical creativity, and the ways in which AI-Music researchers, developers, and entrepreneurs discuss the accessibility of their products can reveal their beliefs about what constitutes musical creativity and how they see users positioned to creatively engage with AI. We propose that a systematic examination of how this concept is deployed by various AI Music companies and research teams could clarify their ideological foundations. In this study, we perform a systematic investigation into 10 Generative-AI Music tools that have been recently released. A diverse range of generative tools will be selected which self-described as creativity-enabling, or provide functionalities that allow the user to engage creatively. First, we collect secondary data in which developers/companies describe their own products. Then we perform an autoethnographic account of our own engagement with the systems and gather user descriptions of their experiences with these systems (as collected from Discords or other channels). Thematic analysis is used to find patterns and incongruities in the system descriptions when positioned against product functionality. Then we triangulate the analyzed data to develop nuanced, contextual descriptions of the tools and their relationships to creative accessibility. Through this investigation, we will identify ideas, beliefs and attitudes that are shaping the early stages of Generative-AI Music to help evaluate their promises and influence their development. This will add to a growing account of the AI Music ecosystem, and build on some of the present and speculative socio-cultural implications of AI Music.