From Multimodal Perception to Strategic Reasoning: A Survey on AI-Generated Game Commentary
Zheng, Qirui, Wang, Xingbo, Cheng, Keyuan, Ali, Muhammad Asif, Lu, Yunlong, Li, Wenxin
–arXiv.org Artificial Intelligence
The advent of artificial intelligence has propelled AI-Generated Game Commentary (AI-GGC) into a rapidly expanding field, offering benefits such as unlimited availability and personalized narration. However, current researches in this area remain fragmented, and a comprehensive survey that systematically unifies existing efforts is still missing. 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. Commentary is further categorized into three functional types: Descriptive, Analytical, and Background. Building on this structure, we provide an in-depth review of state-of-the-art methods, datasets, and evaluation metrics across various game genres. Finally, we highlight key challenges such as real-time reasoning, multimodal integration, and evaluation bottlenecks, and outline promising directions for future research and system development in AI-GGC.
arXiv.org Artificial Intelligence
Oct-21-2025
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