The ICASSP 2026 Automatic Song Aesthetics Evaluation Challenge
Abstract
This paper summarizes the ICASSP 2026 Automatic Song Aesthetics Evaluation (ASAE) Challenge, which focuses on predicting the subjective aesthetic scores of AI-generated songs. The challenge consists of two tracks: Track 1 targets the prediction of the overall musicality score, while Track 2 focuses on predicting five fine-grained aesthetic scores. The challenge attracted strong interest from the research community and received numerous submissions from both academia and industry. Top-performing systems significantly surpassed the official baseline, demonstrating substantial progress in aligning objective metrics with human aesthetic preferences. The outcomes establish a standardized benchmark and advance human-aligned evaluation methodologies for modern music generation systems.
Keywords
Cite
@article{arxiv.2601.07237,
title = {The ICASSP 2026 Automatic Song Aesthetics Evaluation Challenge},
author = {Guobin Ma and Yuxuan Xia and Jixun Yao and Huixin Xue and Hexin Liu and Shuai Wang and Hao Liu and Lei Xie},
journal= {arXiv preprint arXiv:2601.07237},
year = {2026}
}
Comments
Official summary paper for the ICASSP 2026 ASAE Challenge