Accompaniment Prompt Adherence: A Measure for Evaluating Music Accompaniment Systems

Fuente: arXiv
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Auteurs principaux: Grachten, Maarten, Nistal, Javier
Format: Preprint
Publié: 2025
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author Grachten, Maarten
Nistal, Javier
author_facet Grachten, Maarten
Nistal, Javier
contents Generative systems of musical accompaniments are rapidly growing, yet there are no standardized metrics to evaluate how well generations align with the conditional audio prompt. We introduce a distribution-based measure called "Accompaniment Prompt Adherence" (APA), and validate it through objective experiments on synthetic data perturbations, and human listening tests. Results show that APA aligns well with human judgments of adherence and is discriminative to transformations that degrade adherence. We release a Python implementation of the metric using the widely adopted pre-trained CLAP embedding model, offering a valuable tool for evaluating and comparing accompaniment generation systems.
format Preprint
id arxiv_https___arxiv_org_abs_2503_06346
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Accompaniment Prompt Adherence: A Measure for Evaluating Music Accompaniment Systems
Grachten, Maarten
Nistal, Javier
Sound
Audio and Speech Processing
Generative systems of musical accompaniments are rapidly growing, yet there are no standardized metrics to evaluate how well generations align with the conditional audio prompt. We introduce a distribution-based measure called "Accompaniment Prompt Adherence" (APA), and validate it through objective experiments on synthetic data perturbations, and human listening tests. Results show that APA aligns well with human judgments of adherence and is discriminative to transformations that degrade adherence. We release a Python implementation of the metric using the widely adopted pre-trained CLAP embedding model, offering a valuable tool for evaluating and comparing accompaniment generation systems.
title Accompaniment Prompt Adherence: A Measure for Evaluating Music Accompaniment Systems
topic Sound
Audio and Speech Processing
url https://arxiv.org/abs/2503.06346