InsightPulse: An IoT-based System for User Experience Interview Analysis

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.

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Publication Details

Published
2024-10-28
DOI
https://doi.org/10.1109/cic62241.2024.00016
Primary Topic
Big Data and Business Intelligence
Type
article
Field-Weighted Citation Impact
0.00

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article

InsightPulse: An IoT-based System for User Experience Interview Analysis

John Raiti, Yuan Lü, Ri‐hua Xie, Jinhua He et al.
Big Data and Business Intelligence
article

InsightPulse: An IoT-based System for User Experience Interview Analysis

John Raiti, Yuan Lü, Ri‐hua Xie, Jinhua He, Murad Mehrab Abrar, Dian Lyu
article en

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.

George Washington University (US), University of Washington (US), Science Exchange (United States) (US)
University of Washington
Openalex Percentile: Top 59%
Big Data and Business Intelligence
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