Large-Scale User Behavior Analysis in Multimodal AI-Assisted Manual Task Execution

2026-09-07

AI Summary

研究通过分析数千用户在自然环境下的行为，揭示了对话任务助手(CTA)使用中的交互流程、用户意图、对话特征及满意度相关因素，为未来研究提供了设计指导。

Abstract

Conversational Task Assistants (CTAs) are multimodal dialogue systems that support users in complex real-world tasks such as cooking and DIY through voice, text, image, and video interactions. Prior user studies have focused on controlled settings, leaving limited understanding of real-world CTA usage at scale. In this work, we present a large-scale study of CTA usage based on thousands of users in-the-wild. Our large-scale real-world data analysis unveils new understandings of (i) user-CTA interaction flows, (ii) user intents, (iii) user conversational traits, and (iv) behavioral factors associated with user satisfaction. Our findings reveal key opportunities for future research in CTAs, particularly in user interaction design and task engagement, concluding with concrete design guidelines.

Problem

• User Behavior Analysis
• Multimodal AI
• Conversational Task Assistants
• Real-World Usage

Innovation

• Large-Scale Study
• User-CTA Interaction
• Real-World Usage
• Design Guidelines