| 磯 颯 | D, 中間発表 | 自然言語処理学（ソーシャル・コンピューティング） | 松本 裕治☆, 中村 哲, 荒牧 英治, 進藤 裕之, 若宮 翔子 |
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language of the presentation: Japanese
発表題目: 構造データを用いたテキストの生成に関する研究: Learning to Select, Track, and Generate for Data-to-Text 発表概要: We propose a data-to-text generation model with two modules, one for tracking and the other for text generation. Our tracking module selects and keeps track of salient information and memorizes which record has been mentioned. Our generation module generates a summary conditioned on the state of tracking module. Our model is considered to simulate the human-like writing process that gradually selects the information by determining the intermediate variables while writing the summary. In addition, we also explore the effectiveness of the writer information for generation. Experimental results show that our model outperforms existing models in all evaluation metrics even without writer information. Incorporating writer information further improves the performance, contributing to content planning and surface realization. | |||