HCAINov 19, 2025

PresentCoach: Dual-Agent Presentation Coaching through Exemplars and Interactive Feedback

arXiv:2511.15253v12 citationsh-index: 4
Originality Incremental advance
AI Analysis

This work addresses presentation skill development for learners in education and professional contexts, offering a scalable AI tool, though it is incremental as it integrates existing functionalities into a cohesive system.

The authors tackled the problem of limited access to personalized presentation coaching by developing a dual-agent AI system that generates model presentation videos and provides interactive feedback, demonstrating its implementation with multimodal analysis and humanized audience simulation.

Effective presentation skills are essential in education, professional communication, and public speaking, yet learners often lack access to high-quality exemplars or personalized coaching. Existing AI tools typically provide isolated functionalities such as speech scoring or script generation without integrating reference modeling and interactive feedback into a cohesive learning experience. We introduce a dual-agent system that supports presentation practice through two complementary roles: the Ideal Presentation Agent and the Coach Agent. The Ideal Presentation Agent converts user-provided slides into model presentation videos by combining slide processing, visual-language analysis, narration script generation, personalized voice synthesis, and synchronized video assembly. The Coach Agent then evaluates user-recorded presentations against these exemplars, conducting multimodal speech analysis and delivering structured feedback in an Observation-Impact-Suggestion (OIS) format. To enhance the authenticity of the learning experience, the Coach Agent incorporates an Audience Agent, which simulates the perspective of a human listener and provides humanized feedback reflecting audience reactions and engagement. Together, these agents form a closed loop of observation, practice, and feedback. Implemented on a robust backend with multi-model integration, voice cloning, and error handling mechanisms, the system demonstrates how AI-driven agents can provide engaging, human-centered, and scalable support for presentation skill development in both educational and professional contexts.

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