JSAI2024

Presentation information

Organized Session

Organized Session » OS-26

[1G4-OS-26a] OS-26

Tue. May 28, 2024 3:00 PM - 4:40 PM Room G (Room 22+23)

オーガナイザ:福田 賢一郎(産業技術総合研究所)、江上 周作(産業技術総合研究所)、宮田 なつき(産業技術総合研究所)、Qiu Yue(産業技術総合研究所)、鵜飼 孝典(富士通株式会社)、古崎 晃司(大阪電気通信大学)、川村 隆浩(農業・食品産業技術総合研究機構)、市瀬 龍太郎(東京工業大学)、岡田 慧(東京大学)

4:20 PM - 4:40 PM

[1G4-OS-26a-05] Automatic Generation of Soccer Commentary from Play Data Using Rule-based Method

〇Chikara Tanaka1,2, Hiroya Takamura2, Ryutaro Ichise1,2 (1. Tokyo Institute of Technology, 2. National Institute of Advanced Industrial Science and Technology)

Keywords:Data2Text, Text Generation, Soccer

Text commentary on sports websites is manually entered by sports data companies. It’s very convenient for those who cannot watch the live game but want to follow it in real time. However, making it requires a lot of work, especially in soccer, where a large number of events take place in a 90-minute period by players. As a labor-saving method, we propose an AI-based automatic text commentary generation system using Play data which has a time series of events made of numerical data. We compared the capability of two methods, an NN based method proposed in a previous study and a newly proposed Rule-based method, by Automatic evaluation and Human evaluation, respectively. The results show that the Rule based method significantly outperforms the NN-based method in terms of content selection, grammatical accuracy, and proper noun output, indicating the effectiveness for Data2Text task.

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