Towards The Generation Of Musical Explanations With GPT-3 · The Large Language Model Bible Contribute to LLM-Bible

Towards The Generation Of Musical Explanations With GPT-3

Krol Stephen James, Llano Maria Teresa, Mccormack Jon. Artificial Intelligence in Music Sound Art and Design - 2022

[Paper]    
Applications GPT Interpretability And Explainability Model Architecture Prompting

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.

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