The ICASSP 2026 Automatic Song Aesthetics Evaluation Challenge

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Guobin Ma, Yuxuan Xia, Jixun Yao, Huixin Xue, Hexin Liu, Shuai Wang, Hao Liu, Lei Xie

Published: 2026, Last Modified: 26 Mar 2026CoRR 2026EveryoneRevisionsBibTeXCC BY-SA 4.0
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.