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Towards the Generation of Musical Explanations with GPT-3

2022-05-11 13:04:54
Stephen James Krol, Maria Teresa Llano, Jon McCormack
arXiv_AI
           
Abstract

Open AI's language model, GPT-3, has shown great potential for many NLP tasks, with applications in many different domains. In this work we carry out a first study on GPT-3's capability to communicate musical decisions through textual explanations when prompted with a textual representation of a piece of music. Enabling a dialogue in human-AI music partnerships is an important step towards more engaging and creative human-AI interactions. Our results show that GPT-3 lacks the necessary intelligence to really understand musical decisions. A major barrier to reach a better performance is the lack of data that includes explanations of the creative process carried out by artists for musical pieces. We believe such a resource would aid the understanding and collaboration with AI music systems.

Abstract (translated)

URL

https://arxiv.org/abs/2206.08264

PDF

https://arxiv.org/pdf/2206.08264.pdf

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