2024
EMNLP
EMNLP 2024
LM-Interview: An Easy-to-use Smart Interviewer System via Knowledge-guided Language Model Exploitation
Abstract
AbstractSemi-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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Interdisciplinary Bridge
— Artificial Intelligence and Natural Language Processing
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Keyword Pioneer
— interview automation
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Cross-Pollinator
— Artificial Intelligence, Computer Science, Computer Vision, Data Science & Analytics, Deep Learning, Healthcare & Medicine, Interdisciplinary, Knowledge & Reasoning, Machine Learning, Mathematics & Optimization, Natural Language Processing, Reinforcement Learning, Robotics, Security & Privacy, Speech & Audio
Authors
Hanming Li
,
Jifan Yu
,
Ruimiao Li
,
Zhanxin Hao
,
Yan Xuan
,
Jiaxi Yuan
,
Bin Xu
,
Juanzi Li
,
Zhiyuan Liu