# Play Me Something Icy: Practical Challenges, Explainability and the Semantic Gap in Generative AI Music

arXiv: https://arxiv.org/abs/2408.07224 · HTML: https://mlsanity.com/paper/2408.07224/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 4 of its 10 references that are in the map.
- First posted on arXiv 13 Aug 2024.

## Builds on (most cited first, 4 of 4)

- [Music Understanding LLaMA: Advancing Text-to-Music Generation with Question Answering and Captioning](https://mlsanity.com/paper/2308.11276/) (2023)
- [Prompting AI Art: An Investigation into the Creative Skill of Prompt Engineering](https://mlsanity.com/paper/2303.13534/) (2023)
- [AIxArtist: A First-Person Tale of Interacting with Artificial Intelligence to Escape Creative Block](https://mlsanity.com/paper/2308.11424/) (2023)
- [On The Open Prompt Challenge In Conditional Audio Generation](https://mlsanity.com/paper/2311.00897/) (2023)

## Abstract (arXiv)

This pictorial aims to critically consider the nature of text-to-audio and text-to-music generative tools in the context of explainable AI. As a group of experimental musicians and researchers, we are enthusiastic about the creative potential of these tools and have sought to understand and evaluate them from perspectives of prompt creation, control, usability, understandability, explainability of the AI process, and overall aesthetic effectiveness of the results. One of the challenges we have identified that is not explicitly addressed by these tools is the inherent semantic gap in using text-based tools to describe something as abstract as music. Other gaps include explainability vs. useability, and user control and input vs. the human creative process. The aim of this pictorial is to raise questions for discussion and make a few general suggestions on the kinds of improvements we would like to see in generative AI music tools.