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.

翻译：本文概述了 ICASSP 2026 自动歌曲美学评估（ASAE）挑战赛，该挑战赛聚焦于预测 AI 生成歌曲的主观美学评分。挑战赛包含两个赛道：赛道 1 旨在预测整体音乐性评分，而赛道 2 则专注于预测五个细粒度的美学评分。本次挑战赛引起了研究界的浓厚兴趣，并收到了来自学术界和工业界的众多提交。表现优异的系统显著超越了官方基线，表明在使客观指标与人类美学偏好对齐方面取得了实质性进展。这些成果为现代音乐生成系统建立了一个标准化基准，并推进了以人为本的评估方法学。