Talk to Me, Not the Slides: A Real-Time Wearable Assistant for Improving Eye Contact in Presentations

2026-02-01

AI Summary

This work proposes SpeakAssis, the first real-time wearable assistance system designed for authentic public speaking scenarios to address the common challenge novice speakers face in establishing effective eye contact, which often undermines their credibility and audience engagement. Integrating head-mounted eye tracking, scene-level visual analysis, and context-aware audio feedback, SpeakAssis dynamically guides speakers to optimize their gaze distribution during presentations. By continuously modeling real-time gaze patterns, the system delivers contextualized auditory cues that encourage more balanced and intentional eye contact. User studies demonstrate that SpeakAssis increases average eye contact duration by 62.5%, promotes more equitable attention allocation across the audience, and significantly enhances perceived speaker–audience interactivity and engagement.

Technology Category

• Humans and AI: Interaction Techniques and Devices
• Cognitive Modeling & Cognitive Systems: Social Cognition And Interaction
• Computer Vision: Motion & Tracking

Application Category

• Search and Retrieval-Augmented AI: Assisted, interactive, and conversational search
• User Modeling, Personalization and Recommendation: User modeling and simulation for interactive and conversational systems
• Security and Privacy: Large-scale security measurements

Abstract

Effective eye contact is a cornerstone of successful public speaking. It strengthens the speaker's credibility and fosters audience engagement. Yet, managing effective eye contact is a skill that demands extensive training and practice, often posing a significant challenge for novice speakers. In this paper, we present SpeakAssis, the first real-time, in-situ wearable system designed to actively assist speakers in maintaining effective eye contact during live presentations. Leveraging a head-mounted eye tracker for gaze and scene view capture, SpeakAssis continuously monitors and analyzes the speaker's gaze distribution across audience and non-audience regions. When ineffective eye-contact patterns are detected, such as insufficient eye contact, or neglect of certain audience segments, SpeakAssis provides timely, context-aware audio prompts via an earphone to guide the speaker's gaze behavior. We evaluate SpeakAssis through a user study involving eight speakers and 24 audience members. Quantitative results show that SpeakAssis increases speakers'eye-contact duration by 62.5% on average and promotes a more balanced distribution of visual attention. Additionally, statistical analysis based on audience surveys reveals that improvements in speaker's eye-contact behavior significantly enhance the audience's perceived engagement and interactivity during presentations.

Problem

• eye contact
• public speaking
• audience engagement
• gaze behavior
• presentation skills

Innovation

• wearable assistant
• eye contact
• real-time feedback
• gaze tracking
• public speaking