通过人工智能提升工程专业学生的公共演讲技能
Enhancing Public Speaking Skills in Engineering Students Through AI
AI总结：
本文针对工程专业学生公共演讲训练不足的问题，提出融合语音分析、计算机视觉和情感检测的多模态AI评估模型，其中Gemini Pro与专家评估一致性最佳，实现个性化、可扩展的演讲反馈。
摘要：
这篇研究到实践全文论文的灵感来源于工程专业学生在有效沟通方面长期存在的挑战。公共演讲是未来工程师必备的技能，因为他们必须与不同的利益相关者交流技术知识。虽然大学提供课程或工作坊，但无法为学生提供持续且个性化的训练。对公共演讲的语言和非语言方面提供全面反馈非常耗时，使得一致且个性化的评估难以实现。本研究整合了公共演讲中语言和非语言线索的研究，为工程专业学生开发了一个人工智能驱动的评估模型。我们的方法将语音分析、计算机视觉和情感检测结合到一个多模态人工智能系统中，提供评估和反馈。该模型评估（1）语言沟通（音高、响度、节奏、语调），（2）非语言沟通（面部表情、手势、姿势），以及（3）表达一致性，这是一种新颖的整合方式，确保语音与肢体语言之间的对齐。与以往分别评估这些方面的系统不同，我们的模型融合多种模态，提供个性化、可扩展的反馈。初步测试表明，我们的人工智能生成反馈与专家评估具有中等程度的一致性。在所评估的最先进人工智能模型中，全部为大型语言模型（LLMs），包括Gemini和OpenAI模型，Gemini Pro表现最佳，与人类标注者的一致性最强。通过消除对人类评估者的依赖，这个人工智能驱动的公共演讲训练器能够实现反复练习，帮助学生自然地使语音与肢体语言和情感保持一致，这对于有影响力和专业的沟通至关重要。
英文摘要：
This research-to-practice full paper was inspired by the persistent challenge in effective communication among engineering students. Public speaking is a necessary skill for future engineers as they have to communicate technical knowledge with diverse stakeholders. While universities offer courses or workshops, they are unable to offer sustained and personalized training to students. Providing comprehensive feedback on both verbal and non-verbal aspects of public speaking is time-intensive, making consistent and individualized assessment impractical. This study integrates research on verbal and non-verbal cues in public speaking to develop an AI-driven assessment model for engineering students. Our approach combines speech analysis, computer vision, and sentiment detection into a multi-modal AI system that provides assessment and feedback. The model evaluates (1) verbal communication (pitch, loudness, pacing, intonation), (2) non-verbal communication (facial expressions, gestures, posture), and (3) expressive coherence, a novel integration ensuring alignment between speech and body language. Unlike previous systems that assess these aspects separately, our model fuses multiple modalities to deliver personalized, scalable feedback. Preliminary testing demonstrated that our AI-generated feedback was moderately aligned with expert evaluations. Among the state-of-the-art AI models evaluated, all of which were Large Language Models (LLMs), including Gemini and OpenAI models, Gemini Pro emerged as the best-performing, showing the strongest agreement with human annotators. By eliminating reliance on human evaluators, this AI-driven public speaking trainer enables repeated practice, helping students naturally align their speech with body language and emotion, crucial for impactful and professional communication.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
