Analysis of the relationship between user response to dialog breakdown and personality traits
Author:
Affiliation:
1. Graduate School of Information Science and Technology, Aichi Prefectural University, Nagakute, Japan
2. Department of Computer Science and Engineering, Toyohashi University of Technology, Toyohashi, Japan
Publisher
Informa UK Limited
Subject
Computer Science Applications,Hardware and Architecture,Human-Computer Interaction,Software,Control and Systems Engineering
Link
https://www.tandfonline.com/doi/pdf/10.1080/01691864.2023.2279610
Reference14 articles.
1. Higashinaka R D' Haro LF Abu Shawar B et al. Overview of the dialogue breakdown detection challenge 4. In: Marchi E Siniscalchi SM Cumani S Salerno VM and Li H editors. Increasing Naturalness and Flexibility in Spoken Dialogue Interaction: 10th International Workshop on Spoken Dialogue Systems Lecture Notes in Electrical Engineering. Singapore: Springer; 2021. p. 403–417.
2. Kontogiorgos D Tran M Gustafson J et al. A systematic cross-corpus analysis of human reactions to robot conversational failures. In: Proceedings of the 2021 International Conference on Multimodal Interaction. Montréal QC Canada: ACM; Oct 2021. p. 112–120.
3. Tsubokura K Iribe Y Kitaoka N. Dialog breakdown detection using multimodal features for non-task-oriented dialog systems. In: Proceedings of the IEEE GCCE 2022; Oct 2022.
4. Kawamoto A Wada K Kitamura T et al. Preliminary study on detection of behavioral features at conversation breakdown in human-robot interactions. In: 2019 IEEE/SICE International Symposium on System Integration (SII). Paris France: IEEE; Jan 2019. p. 375–378.
5. An G Levitan SI Hirschberg J et al. Deep personality recognition for deception detection. In: Proceedings of Interspeech 2018; 2018.
1.学者识别学者识别
2.学术分析学术分析
3.人才评估人才评估
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