From Multimodal Perception to Strategic Reasoning: A Survey on AI-Generated Game Commentary

From Multimodal Perception to Strategic Reasoning: A Survey on AI-Generated Game Commentary

Qirui Zheng, Xingbo Wang, Keyuan Cheng, Yunlong Lu, Muhammad Asif Ali, Lingfeng Li, Yongyi Wang, Wenxin Li

Proceedings of the Thirty-Fifth International Joint Conference on Artificial Intelligence
Survey Track. Pages 8125-8133. https://doi.org/10.24963/ijcai.2026/901

The advent of artificial intelligence has propelled AI-Generated Game Commentary (AI-GGC) into a rapidly expanding research area, offering advantages such as scalable availability and personalized narration. However, existing studies remain fragmented, and a systematic survey that unifies prior efforts is still lacking. To bridge this gap, our survey introduces a unified framework that systematically organizes the AI-GGC landscape. We present a novel taxonomy focused on three core commentator capabilities: Live Observation, Strategic Analysis, and Historical Recall, and further categorize commentary into three corresponding types: Descriptive Commentary, Analytical Commentary, and Background Commentary. Building on this structure, we provide an in-depth review of methods, datasets, and evaluation metrics, analyzing their strengths and limitations. Finally, we highlight key challenges and point out promising directions for future research in AI-GGC.
Keywords:
Natural Language Processing: Language generation
Natural Language Processing: Resources and evaluation
Machine Learning: Multi-modal learning
Multidisciplinary Topics and Applications: Entertainment