系统梳理AI游戏解说关键技术与方向
From Multimodal Perception to Strategic Reasoning: A Survey on AI-Generated Game Commentary
- 构建三能力三类型统一框架，涵盖实时观察、战略分析与历史回顾
- 首次整合方法、数据集与评估指标，揭示现有研究短板
- 适合关注AI内容生成与游戏智能的学者与开发者
人工智能推动了AI生成游戏解说（AI-GGC）快速发展，具备可扩展性和个性化优势。但现有研究分散，缺乏系统性综述。本文提出统一框架，构建以实时观察、战略分析和历史回溯为核心的三大评论能力，并对应划分描述性、分析性与背景性三类解说。基于此结构，深入评述相关方法、数据集与评估指标，分析其优劣。最后指出关键挑战与未来研究方向。
原文摘要 · Abstract (English)
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.
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