Year: 2024
Type: conference-paper
Abstract: 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.
Authors: Dian Lyu, Yuetong Lu, Jassie He, Murad Mehrab Abrar, Ruijun Xie, John Raiti
Institutions: University of Washington, George Washington University
Language: English
Subfield: Human-Computer Interaction
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
Funder: University of Washington
OpenAlex ID: W4406433523