Conducting efficient and effective user experience (UX) interviews often poses challenges, such as maintaining focus on key topics and managing the duration of interviews and post-interview analyses. To address these issues, this paper introduces InsightPulse, an Internet of Things (IoT)-based hardware and software system designed to streamline and enhance the UX interview process through speech analysis and Artificial Intelligence. InsightPulse provides real-time support during user interviews by automatically identifying and highlighting key discussion points, proactively suggesting follow-up questions, and generating thematic summaries. These features enable more insightful discoveries and help to manage interview duration effectively. Additionally, the system features a robust backend analytics dashboard that simplifies the post-interview review process, thus facilitating the quick extraction of actionable insights and enhancing overall UX research efficiency.
@article{arxiv.2410.00036,
title = {InsightPulse: An IoT-based System for User Experience Interview Analysis},
author = {Dian Lyu and Yuetong Lu and Jassie He and Murad Mehrab Abrar and Ruijun Xie and John Raiti},
journal= {arXiv preprint arXiv:2410.00036},
year = {2024}
}
Comments
Accepted for publication at the 10th IEEE International Conference on Collaboration and Internet Computing (IEEE CIC 2024), Washington D.C., USA