Game Commentary Datasets
The emergence of video captioning makes it possible to automatically generate natural language description for a given video. However, generating detailed video descriptions that incorporate domain-specific information …...
The paper proposes an innovative method for generating cricket commentary. A hybrid model is proposed that combines three types of neural networks: Convolutional Neural Networks (CNN) for image processing, Long …...
In recent years there has been a surge of interest in the natural language prosessing related to the real world, such as symbol grounding, language generation, and nonlinguistic data search by natural language queries. …...
In recent years, there has been a surge of interest in natural language processing related to the real world, such as symbol grounding, language generation, and non-linguistic data search by natural language queries. …...
In recent years, there has been a surge of interest in the natural language processing related to the real world, such as symbol grounding, language generation, and nonlinguistic data search by natural language queries. …...
The chess domain is well-suited for creating an artificial intelligence (AI) system that mimics real-world challenges, including decision-making. Throughout the years, minimal attention has been paid to investigating …...
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, …...
This work presents an automated and novel system for cricket commentary generation by the introduction of event driven approach and image captioning features. The presented system uses artificial intelligence and machine …...
Automated sports commentary is a form of automated narrative. Sports commentary exists to keep the viewer informed and entertained. One way to entertain the viewer is by telling brief stories relevant to the game in …...
Due to the availability of high performance computational devices and enormous video data, deep learning algorithms are assisting for human understandable description of videos. Automatic commentary generation of cricket …...
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 …...
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 …...
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 …...
The level of computer programs has now reached professional strength for many games, even for the game of Go recently. A more difficult task for computer intelligence now is to create a program able to coach human …...
Recent advancements in large language models (LLMs) have unlocked the potential for generating high-quality game commentary. However, producing insightful and engaging commentary for complex games with incomplete …...
Cricket is a famous game in the world where many metrics are introduced and being used to help the coaches and umpires to solve the critical problems. Though different statistics are used to quantify the player’s …...
Learning to generate continuous linguistic descriptions for multi-subject interactive videos in great details has particular applications in team sports auto-narrative. In contrast to traditional video caption, this task …...
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 …...
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 …...
Although basketball games have received broad attention, the forms of game reports and webcast are purely content-based cross-media: texts, videos, snapshots, and performance figures. Analytical narrations of games that …...
We present an approach to automatically generating verbal commentaries for tennis games. We introduce a novel application that requires a combination of techniques from computer vision, natural language processing and …...
We address the task of generating live soccer-match commentaries from play event data. This task has characteristics that (i) each commentary is only partially aligned with events, (ii) play event data contains many …...
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 …...
Despite the recent emergence of video captioning models, how to generate vivid, fine-grained video descriptions based on the background knowledge (i.e., long and informative commentary about the domain-specific scenes …...
This paper describes a machine learning-based approach for generating natural language comments on Shogi games. We generate comments by using a discriminative language model trained with a large amount of Shogi game …...
This paper examines the problem of generating natural language descriptions of chess games. We introduce a new large-scale chess commentary dataset and propose methods to generate commentary for individual moves in a …...
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. …...
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 …...
Soccer is a globally popular sport with a vast audience, in this paper, we consider constructing an automatic soccer game commentary model to improve the audiences’ viewing experience. In general, we make the …...
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, …...
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 …...
With the growth in applications of Artificial Intelligence day by day, every domain is going automated. Machine learning has enabled systems to learn the process on its own in order to reduce the human labour. In sports …...
Soccer videos are a rich playground for computer vision, involving many elements, such as players, lines, and specific objects. Hence, to capture the richness of this sport and allow for fine automated analyses, we …...
We present SentiMATE, a novel end-to-end Deep Learning model for Chess, employing Natural Language Processing that aims to learn an effective evaluation function assessing move quality. This function is pre-trained on …...
In the pursuit of natural language understanding, there has been a long standing interest in tracking state changes throughout narratives. Impressive progress has been made in modeling the state of transaction-centric …...
Soccer is more than just a game - it is a passion that transcends borders and unites people worldwide. From the roar of the crowds to the excitement of the commentators, every moment of a soccer match is a thrill. Yet, …...
The application of Automatic Speech Recognition (ASR) technology in soccer enables sports analytics by extracting audio commentaries to provide insights into game events and facilitate automatic game understanding. This …...
Understanding broadcast videos is a challenging task in computer vision, as it requires generic reasoning capabilities to appreciate the content offered by the video editing. In this work, we propose SoccerNet-v2, a …...
In this paper, we introduce SoccerNet, a benchmark for action spotting in soccer videos. The dataset is composed of 500 complete soccer games from six main European leagues, covering three seasons from 2014 to 2017 and a …...
Automated sports commentary is a form of automated narrative. Sports commentary exists to keep the viewer informed and entertained. One way to entertain the viewer is by telling brief stories relevant to the game in …...
During a cricket match, commentary keeps the viewers entertained and updated about the game. Quoting relevant stories related to the current game scenario makes the game more interesting. But the knowledge of …...
This paper introduces a new video understanding dataset which can be utilised for the related problems of event recognition, localisation and description in video. Our dataset consists of dense, well structured event …...
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 …...
We present a new dataset containing 10K human-annotated games of Go and show how these natural language annotations can be used as a tool for model interpretability. Given a board state and its associated comment, our …...