Dialog State Tracking and action selection using deep learning mechanism for interview coaching

Ming Hsiang Su, Kun Yi Huang, Tsung Hsien Yang, Kuan Jung Lai, Chung Hsien Wu

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

3 Citations (Scopus)

Abstract

The best way to prepare for an interview is to review the different types of possible interview questions you will be asked during an interview and practice responding to questions. An interview coaching system tries to simulate an interviewer to provide mock interview practice simulation sessions for the users. The traditional interview coaching systems provide some feedbacks, including facial preference, head nodding, response time, speaking rate, and volume, to let users know their own performance in the mock interview. But most of these systems are trained with insufficient dialog data and provide the pre-designed interview questions. In this study, we propose an approach to dialog state tracking and action selection based on deep learning methods. First, the interview corpus in this study is collected from 12 participants, and is annotated with dialog states and actions. Next, a long-short term memory and an artificial neural network are employed to predict dialog states and the Deep RL is adopted to learn the relation between dialog states and actions. Finally, the selected action is used to generate the interview question for interview practice. To evaluate the proposed method in action selection, an interview coaching system is constructed. Experimental results show the effectiveness of the proposed method for dialog state tracking and action selection.

Original languageEnglish
Title of host publicationProceedings of the 2016 International Conference on Asian Language Processing, IALP 2016
EditorsMinghui Dong, Chung-Hsien Wu, Yanfeng Lu, Haizhou Li, Yuen-Hsien Tseng, Liang-Chih Yu, Lung-Hao Lee
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages6-9
Number of pages4
ISBN (Electronic)9781509009213
DOIs
Publication statusPublished - 2017 Mar 10
Event20th International Conference on Asian Language Processing, IALP 2016 - Tainan, Taiwan
Duration: 2016 Nov 212016 Nov 23

Publication series

NameProceedings of the 2016 International Conference on Asian Language Processing, IALP 2016

Other

Other20th International Conference on Asian Language Processing, IALP 2016
CountryTaiwan
CityTainan
Period16-11-2116-11-23

All Science Journal Classification (ASJC) codes

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

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  • Cite this

    Su, M. H., Huang, K. Y., Yang, T. H., Lai, K. J., & Wu, C. H. (2017). Dialog State Tracking and action selection using deep learning mechanism for interview coaching. In M. Dong, C-H. Wu, Y. Lu, H. Li, Y-H. Tseng, L-C. Yu, & L-H. Lee (Eds.), Proceedings of the 2016 International Conference on Asian Language Processing, IALP 2016 (pp. 6-9). [7875922] (Proceedings of the 2016 International Conference on Asian Language Processing, IALP 2016). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/IALP.2016.7875922