Date
Publisher
arXiv
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.
Study at a glance
- Question: Can a dual-agent AI coaching system reduce public-speaking anxiety while keeping cognitive workload manageable?
- Setting and data: University laboratory setting, 24 native Mandarin-speaking non-native English speakers aged 19–25.
- Method: Controlled between-subjects lab experiment with pre- and post-tests, surveys, and semi-structured interviews.
Why it matters
Learners often lack access to high-quality exemplars or personalized coaching for public speaking. Existing AI tools typically offer isolated metrics or script generation without integrating reference modeling and interactive feedback into a cohesive learning experience.
Key findings
- Rehearsal with PresentCoach significantly increased speaking confidence on the PRCS scale compared with self-directed practice, with scores rising by 36.3% versus 16.1%.
- Participants experienced only a moderate cognitive workload (2.9 out of 7 on NASA-TLX) and reported high system usability (4.1 out of 5 on the SUS scale).
- Learners positively differentiated the two agents' roles, noting that the exemplar video provided clear targets while the coach delivered empathetic, actionable guidance.
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