Sentence Punctuation for Collaborative Commentary Generation in Esports Live-Streaming
Hong Huang, Junjie H. Xu, Xiaoling Ling, Pujana Paliyawan

TL;DR
This paper introduces two strategies for sentence punctuation in Esports live-streaming commentary, improving the quality of generated collaborative commentary through experiments with a pre-trained language model.
Contribution
The paper proposes novel punctuation strategies for game commentary text sequences and demonstrates their effectiveness over baseline methods.
Findings
Two-sequence punctuation strategy outperforms baseline in automatic metrics.
Fine-tuning a pre-trained language model enhances commentary generation.
Objective and subjective evaluations confirm the strategy's effectiveness.
Abstract
To solve the existing sentence punctuation problem for collaborative commentary generation in Esports live-streaming, this paper presents two strategies for sentence punctuation for text sequences of game commentary, that is, punctuating sentences by two or three text sequence(s) originally punctuated by Youtube to obtain a complete sentence of commentary. We conducted comparative experiments utilizing and fine-tuning a state-of-the-art pre-trained generative language model among two strategies and the baseline to generate collaborative commentary. Both objective evaluations by automatic metrics and subjective analyses showed that our strategy of punctuating sentences by two text sequences outperformed the baseline.
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsTopic Modeling · Natural Language Processing Techniques · Artificial Intelligence in Games
