Hanming Li


2024

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LM-Interview: An Easy-to-use Smart Interviewer System via Knowledge-guided Language Model Exploitation
Hanming Li | Jifan Yu | Ruimiao Li | Zhanxin Hao | Yan Xuan | Jiaxi Yuan | Bin Xu | 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.