用双智能体系统模拟优秀演讲并实时反馈，提升演讲训练效果。
PresentCoach: Dual-Agent Presentation Coaching through Exemplars and Interactive Feedback
- 双智能体协作：一个生成示范视频，一个评估用户表现并提建议。
- 反馈采用观察-影响-建议结构，结合观众视角提升真实感。
- 适合需要提升演讲能力的教育与职场人士，支持个性化练习。
有效的演讲能力在教育、职业沟通和公共演讲中至关重要，但学习者往往缺乏高质量范例或个性化辅导。现有AI工具通常仅提供语音评分或脚本生成等单一功能，未能将参考建模与互动反馈整合为连贯的学习体验。我们提出一种双智能体系统，通过两个互补角色支持演讲练习：理想演讲代理（Ideal Presentation Agent）将用户提供的幻灯片转化为示范视频，整合幻灯片处理、视觉语言分析、叙述脚本生成、个性化语音合成与同步视频拼接；教练代理（Coach Agent）则对比用户录制的演讲进行多模态分析，并以观察-影响-建议（OIS）格式输出结构化反馈。为增强学习体验的真实性，教练代理还引入观众代理（Audience Agent），模拟人类听众视角，提供反映观众反应与参与度的人性化反馈。两者构成观察、实践与反馈的闭环。系统基于强大的后端架构，集成多模型、语音克隆与错误处理机制，展示了人工智能驱动的智能体如何在教育与职业场景中，为演讲技能发展提供沉浸式、以人为中心且可扩展的支持。
原文摘要 · Abstract (English)
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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