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Welcome to attend IEEE ICASSP 2026 Grand Challenge (GC)
GC-2: Automatic Song Aesthetics Evaluation
Organized by: Ting Dang, Haohe Liu, Hao Liu, Hexin Liu, Lei Xie, Huixin Xue, Wei Xue, Guobin Ma, Hao Shi, Yui Sudo, Jixun Yao, Ruibin Yuan, Jingyao Wu, Wenwu Wang
Challenge website: https://aslp-lab.github.io/Automatic-Song-Aesthetics-Evaluation-Challenge/
ICASSP 2026 website: https://2026.ieeeicassp.org/
Title: Automatic Song Aesthetics Evaluation Challenge
Short description: Recent advances in generative music models have enabled automatic song creation with impressive quality and diversity, powering applications from virtual artists to movie dubbing. However, evaluating the aesthetic quality of generated
songs, capturing factors like emotional expressiveness, musicality, and listener enjoyment, remains a key challenge. Existing metrics often fail to reflect human perception. To address this gap, the Automatic Song Aesthetics Evaluation Challenge invites participants
to develop models that predict human ratings of song aesthetics based solely on audio. This competition aims to establish a standardized benchmark for assessing musical aesthetics in song generation, with human-annotated datasets and a focus on listener-centered
criteria. By bridging signal processing, affective computing, and machine learning, this challenge seeks to drive progress toward more human-aligned music generation and evaluation.
Timeline
Thanks for your attention. Sorry for cross-posting.
Best wishes,
Wenwu -- Wenwu Wang
Professor of Signal Processing and Machine Learning,
Centre for Vision Speech and Signal Processing (CVSSP)
Associate Head of External Engagement,
School of Computer Science and Electronic Engineering
AI Fellow,
Surrey Institute for People Centred AI
University of Surrey
Guildford, GU2 7XH
United Kingdom Phone: +44 (0) 1483 686039 Fax: +44 (0) 1483 686031 Email: w.wang@xxxxxxxxxxxx |