Automatic template feature extraction and the application to utterance in a dialogue system

Yoshitaka Mikami, Masafumi Hagiwara

研究成果: Conference contribution

抄録

In this paper, we propose an automatic template features extraction method and apply it to utterance generation in a dialogue system. Template-based utterance generation has been widely used in many dialogue systems because of its robustness. Although variety of templates and the appropriate selection are crucial points in the method, they have not been paid attention so far. This paper focuses on the points; first, we propose the new neural network model utilizingLSTM (Long Short-Term Memory) to extract effective and unique features for templates, and then applied it to utterance generation in a dialogue system. To examine the effectiveness of the proposed method, we conduct two kinds of experiments; subjective evaluation and dialogue breakdown detection experiment. In both of the experiments, the proposed method has shown higher accuracy than the conventional methods.

本文言語English
ホスト出版物のタイトル2nd International Conference on Machine Learning and Soft Computing, ICMLSC 2018
出版社Association for Computing Machinery
ページ164-168
ページ数5
ISBN(電子版)9781450363365
DOI
出版ステータスPublished - 2018 2 2
イベント2nd International Conference on Machine Learning and Soft Computing, ICMLSC 2018 - Phu Quoc Island, Viet Nam
継続期間: 2018 2 22018 2 4

Other

Other2nd International Conference on Machine Learning and Soft Computing, ICMLSC 2018
CountryViet Nam
CityPhu Quoc Island
Period18/2/218/2/4

ASJC Scopus subject areas

  • Human-Computer Interaction
  • Computer Networks and Communications
  • Computer Vision and Pattern Recognition
  • Software

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