Yan Xuan
2024
LM-Interview: An Easy-to-use Smart Interviewer System via Knowledge-guided Language Model Exploitation
Hanming Li
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Jifan Yu
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Ruimiao Li
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Zhanxin Hao
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Yan Xuan
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Jiaxi Yuan
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Bin Xu
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Juanzi Li
|
Zhiyuan Liu
Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing: System Demonstrations
Semi-structured interviews are a crucial method of data acquisition in qualitative research. Typically controlled by the interviewer, the process progresses through a question-and-answer format, aimed at eliciting information from the interviewee. However, interviews are highly time-consuming and demand considerable experience of the interviewers, which greatly limits the efficiency and feasibility of data collection. Therefore, we introduce LM-Interview, a novel system designed to automate the process of preparing, conducting and analyzing semi-structured interviews. Experimental results demonstrate that LM-interview achieves performance comparable to that of skilled human interviewers.
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Co-authors
- Hanming Li 1
- Jifan Yu 1
- Ruimiao Li 1
- Zhanxin Hao 1
- Jiaxi Yuan 1
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