- 著者
-
井上 昂治
原 康平
ララ ディベッシュ
中村 静
高梨 克也
河原 達也
- 出版者
- 一般社団法人 人工知能学会
- 雑誌
- 人工知能学会論文誌 (ISSN:13460714)
- 巻号頁・発行日
- vol.35, no.5, pp.D-K43_1-10, 2020-09-01 (Released:2020-09-01)
- 参考文献数
- 32
A spoken dialogue system that plays the role of an interviewer for job interviews is presented. In this work, ourgoal is to implement an automated job interview system where candidates can use it as practice before the real interview.Conventional job interview systems ask only pre-defined questions, which make the dialogue monotonous andfar from human-human interviews. We propose follow-up question generation based on the assessment of candidateresponses and keyword extraction. This model was integrated into the dialogue system of the autonomous androidERICA to conduct subject experiments. The proposed job interview system was compared with the baseline systemthat did not generate any follow-up questions and selected among pre-defined questions. The experimental resultsshow that the proposed system is significantly better in subjective evaluations regarding impressions of job interviewpractice, the quality of questions, and the presence of the interviewer.