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Autori principali: Zheng, Qirui, Wang, Xingbo, Cheng, Keyuan, Ali, Muhammad Asif, Lu, Yunlong, Li, Wenxin
Natura: Preprint
Pubblicazione: 2025
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Accesso online:https://arxiv.org/abs/2506.17294
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author Zheng, Qirui
Wang, Xingbo
Cheng, Keyuan
Ali, Muhammad Asif
Lu, Yunlong
Li, Wenxin
author_facet Zheng, Qirui
Wang, Xingbo
Cheng, Keyuan
Ali, Muhammad Asif
Lu, Yunlong
Li, Wenxin
contents 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.
format Preprint
id arxiv_https___arxiv_org_abs_2506_17294
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle 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
Computation and Language
Artificial Intelligence
Machine Learning
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.
title From Multimodal Perception to Strategic Reasoning: A Survey on AI-Generated Game Commentary
topic Computation and Language
Artificial Intelligence
Machine Learning
url https://arxiv.org/abs/2506.17294