Composers' Evaluations of an AI Music Tool: Insights for Human-Centred Design

Eleanor Row, György Fazekas
12/14/2024
cs.SDcs.AIcs.HC

No confident code implementation found for this paper. 1 possible match can be shown below.

Abstract

We present a study that explores the role of user-centred design in developing Generative AI (GenAI) tools for music composition. Through semi-structured interviews with professional composers, we gathered insights on a novel generative model for creating variations, highlighting concerns around trust, transparency, and ethical design. The findings helped form a feedback loop, guiding improvements to the model that emphasised traceability, transparency and explainability. They also revealed new areas for innovation, including novel features for controllability and research questions on the ethical and practical implementation of GenAI models.

View on arXivView PDF

Code Implementations

No confident code match yet

We couldn't find an author-owned or strongly-evidenced community implementation for this paper. 1 weaker match is hidden by default — verify before relying on them.

No code implementations found yet.

Know of an implementation? Let us know in the comments below!

Similar Papers

Evaluating Human-AI Interaction via Usability, User Experience and Acceptance Measures for MMM-C: A Creative AI System for Music Composition

83% match2025

Generative AI for Music and Audio

82% match2024

MusicAIR: A Multimodal AI Music Generation Framework Powered by an Algorithm-Driven Core

82% match2025

Artificial Intelligence Agents in Music Analysis: An Integrative Perspective Based on Two Use Cases

81% match2025

Survey on the Evaluation of Generative Models in Music

80% match2025

MusGO: A Community-Driven Framework For Assessing Openness in Music-Generative AI

80% match2025

Cite this paper

@article{row2024composers,
  title  = {Composers' Evaluations of an AI Music Tool: Insights for Human-Centred Design},
  author = {Eleanor Row and György Fazekas},
  year   = {2024},
  eprint = {2412.10968},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2412.10968v1}
}

Add a badge to your README

Shows whether official code is linked for this paper.

Code of Paper badge
[![Code of Paper](https://codeofpaper.com/badge/2412.10968.svg)](https://codeofpaper.com/paper/2412.10968)

Discussion