Low-Latency Real-Time Audio Game Commentary System via LLM-Based Parallel Text Generation
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Abstract (arXiv)
We present a low-latency real-time audio game commentary system that generates spoken commentary directly from live gameplay video. In this end-to-end setting, a key bottleneck is accumulated waiting time; conventional pipelines capture frames, generate text, and synthesize speech sequentially for each utterance, and do not request the next generation until speech playback has completed. This strict sequentiality causes long and unnatural silence between utterances. To address this latency bottleneck, our system runs text generation in parallel with speech playback and buffers multiple candidate utterances ahead of time, enabling immediate synthesis at playback boundaries. Experiments on fast-paced game videos show that our parallel design reduces the mean inter-utterance silence from 9.6 seconds to 0.3 seconds compared to sequential baselines. It also improves similarity to professional speaking--silence timing patterns by over 40 %, and a user study with 120 experienced game players confirms significantly improved perceived speaking rhythm. Our demo video is available at: https://youtu.be/pmrRUlvav8M.
Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 5 of its 21 references that are in the map. First posted on arXiv 11 Jun 2026.
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References · 5
- 2024Streaming Dense Video Captioningcited by 82
- 2024MatchTime: Towards Automatic Soccer Game Commentary Generationcited by 37
- 2021Fighting Game Commentator with Pitch and Loudness Adjustment Utilizing Highlight Cuescited by 4
- 2025From Multimodal Perception to Strategic Reasoning: A Survey on AI-Generated Game Commentarycited by 3
- 2026Real-Time Generation of Game Video Commentary with Multimodal LLMs: Pause-Aware Decoding Approachescited by 1
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