# Sentence Punctuation for Collaborative Commentary Generation in Esports Live-Streaming

arXiv: https://arxiv.org/abs/2110.12416 · HTML: https://mlsanity.com/paper/2110.12416/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- Builds on 2 of its 10 references that are in the map.
- First posted on arXiv 24 Oct 2021.

## Builds on (most cited first, 2 of 2)

- [Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer](https://mlsanity.com/paper/1910.10683/) (2019)
- [Fighting Game Commentator with Pitch and Loudness Adjustment Utilizing Highlight Cues](https://mlsanity.com/paper/2108.08112/) (2021)

## Built on by (most cited first, 1 of 1)

- [CS-lol: a Dataset of Viewer Comment with Scene in E-sports Live-streaming](https://mlsanity.com/paper/2301.06876/) (2023)

## Abstract (arXiv)

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.