Esports

Audio Commentary System for Real-Time Racing Game Play INLG 2023

Live commentaries are essential for enhancing spectators’ enjoyment and understanding during sports events or e-sports streams. We introduce a live audio commentator system designed specifically for a racing game, …...

Commentary Generation from Data Records of Multiplayer Strategy Esports Game NAACL 2024

Esports, a sports competition on video games, has become one of the most important sporting events. Although esports play logs have been accumulated, only a small portion of them accompany text commentaries for the …...

Conceptual Representation and Evaluation of an FPS Game Commentary Generator ICIPRob 2022

Playing video games has been popular across all the age limits of modern society. In the beginning, it was limited among the younger community and it was just a hobby limited to individuals. Even though the majority of …...

CS-lol: a Dataset of Viewer Comment with Scene in E-sports Live-streaming CHIIR 2023

Billions of live-streaming viewers share their opinions on scenes they are watching in real-time and interact with the event, commentators as well as other viewers via text comments. Thus, there is necessary to explore …...

From eSports Data to Game Commentary: Datasets, Models, and Evaluation Metrics DEIM 2021

Electronic sports (eSports), the sport competition using video games, has become one of the most popular sporting events now. The eSports audience needs textual commentaries for deeply understanding the games and for …...

Game-MUG: Multimodal Oriented Game Situation Understanding and Commentary Generation Dataset Arxiv 2024

The dynamic nature of esports makes the situation relatively complicated for average viewers. Esports broadcasting involves game expert casters, but the caster-dependent game commentary is not enough to fully understand …...

Generating Racing Game Commentary from Vision, Language, and Structured Data INLG 2021

We propose the task of automatically generating commentaries for races in a motor racing game, from vision, structured numerical, and textual data. Commentaries provide information to support spectators in understanding …...

Learning to sportscast: a test of grounded language acquisition ICML 2008

We present a novel commentator system that learns language from sportscasts of simulated soccer games. The system learns to parse and generate commentaries without any engineered knowledge about the English language. …...

LoL-V2T: Large-Scale Esports Video Description Dataset CVPRW 2021

Esports is a fastest-growing new field with a largely online-presence, and is creating a demand for automatic domain-specific captioning tools. However, at the current time, there are few approaches that tackle the …...

MOBA-E2C: Generating MOBA Game Commentaries via Capturing Highlight Events from the Meta-Data EMNLP 2022

MOBA (Multiplayer Online Battle Arena) games such as Dota2 are currently one of the most popular e-sports gaming genres. Following professional commentaries is a great way to understand and enjoy a MOBA game. However, …...

Multimodal Joint Emotion and Game Context Recognition in League of Legends Livestreams COG 2019

Video game streaming provides the viewer with a rich set of audio-visual data, conveying information both with regards to the game itself, through game footage and audio, as well as the streamer’s emotional state …...

Training a Multilingual Sportscaster: Using Perceptual Context to Learn Language JAIR 2010

We present a novel framework for learning to interpret and generate language using only perceptual context as supervision. We demonstrate its capabilities by developing a system that learns to sportscast simulated robot …...