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

arXiv: https://arxiv.org/abs/2410.00036 · HTML: https://mlsanity.com/paper/2410.00036/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 2 of its 18 references that are in the map.
- First posted on arXiv 23 Sep 2024.

## Builds on (most cited first, 2 of 2)

- [Towards A Rigorous Science of Interpretable Machine Learning](https://mlsanity.com/paper/1702.08608/) (2017)
- [Quantized Transformer Language Model Implementations on Edge Devices](https://mlsanity.com/paper/2310.03971/) (2023)

## Abstract (arXiv)

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.