Designing an AI-creativity music course
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Yee-King, Matthew; d'Inverno, Mark and Fiorucci, Andrea. 2024. 'Designing an AI-creativity music course'. In: AIMC 2024. Oxford, United Kingdom 9 - 11 September 2024. [Conference or Workshop Item]
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Abstract or Description
This article describes and evaluates an online generative AI course. The course is based on three AI models combined into a pop song-generating system. A fine-tuned GPT-2 model writes lyrics, Music-VAE composes musical scores and instrumentation and Diffsinger synthesises a singing voice. We explain the decisions made in designing the course, which is based on Piagetian constructivist ‘learning-by-doing’. We present details of the five-week course design with learning objectives, technical concepts, and creative and technical activities. We explain how we overcame technical challenges to build a complete pop song generator system consisting of Python scripts, pre-trained models, and Javascript code, all of which runs in a dockerised Linux container via a web-based IDE. A quantitative analysis of student activity provides evidence of engagement and a benchmark for future improvements. A qualitative analysis of a workshop with experts validated the overall course design, and it suggested the need for a stronger creative brief and much clearer and detailed ethical and legal content.
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Item Type: |
Conference or Workshop Item (Paper) |
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| Keywords: |
gen-AI, AI-music, pedagogy |
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| Event Location: |
Oxford, United Kingdom |
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| Date range: |
9 - 11 September 2024 |
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| Item ID: |
37522 |
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| Date Deposited: |
09 Sep 2024 15:22 |
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| Last Modified: |
09 Sep 2024 15:22 |
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