mlsanityData to 14 Oct 2026

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

arXiv 2506.17294 ↗First posted 17 Jun 2025cs.CL cs.AI cs.LGcited by 3

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Abstract (arXiv)

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.

Key facts. Cited by 3 papers in the map (data through 14 Oct 2026). Builds on 43 of its 106 references that are in the map. First posted on arXiv 17 Jun 2025.

Builds on

43 of 106 references.

References · 43

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31 more
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Built on by

Cited by year (2026 to 14 Oct)

Citing papers per year: 2026: 3.

3 papers.

  1. 2026Low-Latency Real-Time Audio Game Commentary System via LLM-Based Parallel Text Generationcited by 0
  2. 2026An LLM-Based Automatic Sportscast Solution for Robot Soccer Matchescited by 0
  3. 2026GameCommBench: A Unified Benchmark and Type-Aware Evaluation for AI-Generated Game Commentarycited by 0