---
title: "From Multimodal Perception to Strategic Reasoning: A Survey on AI-Generated Game Commentary"
authors:
  - "Qirui Zheng"
  - "Xingbo Wang"
  - "Keyuan Cheng"
  - "Yunlong Lu"
  - "Muhammad Asif Ali"
  - "Lingfeng Li"
  - "Yongyi Wang"
  - "Wenxin Li"
doi: "10.24963/ijcai.2026/901"
url: "https://ijcai.org/proceedings/2026/901"
pdf: "https://ijcai.org/proceedings/2026/0901.pdf"
venue: "Proceedings of the Thirty-Fifth International Joint Conference on Artificial Intelligence"
year: 2026
pages: "8125-8133"
track: "Survey Track"
keywords:
  - "Natural Language Processing: Resources and evaluation"
  - "Natural Language Processing: Language generation"
  - "Machine Learning: Multi-modal learning"
  - "Multidisciplinary Topics and Applications: Entertainment"
---

# 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*, pages 8125-8133. DOI: [10.24963/ijcai.2026/901](https://doi.org/10.24963/ijcai.2026/901)

## Abstract

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.