Dialog state tracking for interview coaching using two-level LSTM

Ming Hsiang Su, Chung Hsien Wu, Kun Yi Huang, Tsung Hsien Yang, Tsui Ching Huang

Research output: Chapter in Book/Report/Conference proceedingConference contribution

3 Citations (Scopus)

Abstract

This study presents an approach to dialog state tracking (DST) in an interview conversation by using the long short-term memory (LSTM) and artificial neural network (ANN). First, the techniques of word embedding are employed for word representation by using the word2vec model. Then, each input sentence is represented by a sentence hidden vector using the LSTM-based sentence model. The sentence hidden vectors for each sentence are fed to the LSTM-based answer model to map the interviewee's answer to an answer hidden vector. For dialog state detection, the answer hidden vector is finally used to detect the dialog state using an ANN-based dialog state detection model. To evaluate the proposed method, an interview conversation system was constructed, and an average accuracy of 89.93% was obtained for dialog state detection.

Original languageEnglish
Title of host publicationProceedings of 2016 10th International Symposium on Chinese Spoken Language Processing, ISCSLP 2016
EditorsHsin-Min Wang, Qingzhi Hou, Yuan Wei, Tan Lee, Jianguo Wei, Lei Xie, Hui Feng, Jianwu Dang, Jianwu Dang
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781509042937
DOIs
Publication statusPublished - 2017 May 2
Event10th International Symposium on Chinese Spoken Language Processing, ISCSLP 2016 - Tianjin, China
Duration: 2016 Oct 172016 Oct 20

Publication series

NameProceedings of 2016 10th International Symposium on Chinese Spoken Language Processing, ISCSLP 2016

Other

Other10th International Symposium on Chinese Spoken Language Processing, ISCSLP 2016
CountryChina
CityTianjin
Period16-10-1716-10-20

All Science Journal Classification (ASJC) codes

  • Signal Processing
  • Computer Vision and Pattern Recognition
  • Linguistics and Language

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  • Cite this

    Su, M. H., Wu, C. H., Huang, K. Y., Yang, T. H., & Huang, T. C. (2017). Dialog state tracking for interview coaching using two-level LSTM. In H-M. Wang, Q. Hou, Y. Wei, T. Lee, J. Wei, L. Xie, H. Feng, J. Dang, & J. Dang (Eds.), Proceedings of 2016 10th International Symposium on Chinese Spoken Language Processing, ISCSLP 2016 [7918438] (Proceedings of 2016 10th International Symposium on Chinese Spoken Language Processing, ISCSLP 2016). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ISCSLP.2016.7918438