GameCommBench: A Unified Benchmark and Type-Aware Evaluation for AI-Generated Game Commentary
cs.AI, cs.CL
Submitted: 2026-10-08
Updated: 2026-10-08
License: http://creativecommons.org/licenses/by/4.0/
The gist: Game commentary is an open-ended generation task requiring multimodal perception, strategic reasoning, and contextual knowledge.
Terminology
Abstract
Game commentary is an open-ended generation task requiring multimodal perception, strategic reasoning, and contextual knowledge. Existing AI-Generated Game Commentary (AI-GGC) studies remain fragmented across games, modalities, and evaluation protocols, while overlap-based or holistic evaluators fail to capture the functional heterogeneity of commentary. We introduce GameCommBench, a unified benchmark spanning board games, sports, and esports, with commentary aligned to heterogeneous game contexts and annotated by commentary type. We further propose Type-Aware Commentary Evaluation (TACE), a structured framework for evaluating different types of commentary. We then validate TACE for reliability and human agreement, and use it to benchmark representative AI commentators. Results reveal non-uniform capability profiles, with live observation and strategic analysis emerging as major bottlenecks. Together, GameCommBench and TACE provide a diagnostic foundation for comparable and interpretable AI-GGC evaluation.
Sources
- WhisperX: Time-Accurate Speech Transcription of Long-Form Audio
- Improving Chess Commentaries by Combining Language Models with Symbolic Reasoning Engines
- ChessQA: Evaluating Large Language Models for Chess Understanding
- Game-MUG: Multimodal Oriented Game Situation Understanding and Commentary Generation Dataset
- From Multimodal Perception to Strategic Reasoning: A Survey on AI-Generated Game Commentary
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