人工知能学会論文誌
Online ISSN : 1346-8030
Print ISSN : 1346-0714
原著論文
ニューラルネットワークを用いた雑談対話からのユーザの興味推定
稲葉 通将高橋 健一
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ジャーナル フリー

2019 年 34 巻 2 号 p. E-I94_1-9

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Non-task-oriented dialogue systems are required to chat with users in accordance with their interests. In this study, we propose a neural network-based method for estimating speakers’ levels of interest from dialogues. Our model first converts given utterances into utterance vectors using a word sequence encoder with word attention. Afterward, our novel attention approach, sentence-specific sentence attention extracts useful information for estimating the level of interest. Additionally, we introduce a new pre-training method for our model. Experimental results indicated that it was most effective to use topic-specific sentence attention and proposed pre-training in combination.

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© 人工知能学会 2019
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