Towards the generation of musical explanations with GPT-3

Stephen James Krol, Maria Teresa Llano, Jon McCormack

Research output: Chapter in Book/Report/Conference proceedingConference PaperResearchpeer-review

1 Citation (Scopus)


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.

Original languageEnglish
Title of host publication11th International Conference, EvoMUSART 2022 Held as Part of EvoStar 2022 Madrid, Spain, April 20–22, 2022 Proceedings
EditorsTiago Martins, Nereida Rodríguez-Fernández, Sérgio M. Rebelo
Place of PublicationCham Switzerland
Number of pages17
ISBN (Electronic)9783031037894
ISBN (Print)9783031037887
Publication statusPublished - 2022
EventInternational Conference on Evolutionary and Biologically Inspired Music, Sound, Art and Design 2022 - Madrid, Spain
Duration: 20 Apr 202222 Apr 2022
Conference number: 11th (Proceedings) (Website)

Publication series

NameLecture Notes in Computer Science
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


ConferenceInternational Conference on Evolutionary and Biologically Inspired Music, Sound, Art and Design 2022
Abbreviated titleEvoMUSART 2022
Internet address


  • Explainability
  • GPT3
  • Music

Cite this