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arXiv · 2601.07237

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.

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BibTeXRIS

Guobin Ma, Yuxuan Xia, Jixun Yao, Huixin Xue, Hexin Liu, Shuai Wang, Hao Liu, Lei Xie. 2026-01-12. The ICASSP 2026 Automatic Song Aesthetics Evaluation Challenge. https://arxiv.org/abs/2601.07237

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