SBIR Phase II: Automated Public Speaking Assessment

这个第二阶段的项目旨在开发软件来自动评估公众演讲技能，并为学生提供更好的口头沟通能力，以完成工作任务。口语表达是整个经济中最受重视的能力，在高工资、高增长、高技能的职业中，口语表达是第二受重视的技能。每年大约有450万大学生学习基础的交流课程，然而，随着班级规模的扩大和在线学习的普及，公开演讲教学变得越来越困难。实践和反馈是这些课程的重要方面，但教师很难找到足够的时间与学生充分互动。这个SBIR项目旨在开发自动公开演讲评估的关键概念，以便学生？S的声音传递可以客观地测量，并以一种创造独立、个性化学习体验的方式呈现。与传统的公开演讲评估方法不同，该系统可以随时使用，提供客观的反馈，并跟踪学生的练习和进步。拟议中的软件即服务预计将在五年内产生1600万美元的收入，并在美国创造超过25个高薪工作岗位。这个小企业创新研究（SBIR）第二阶段项目提议开发一个公共演讲的自动评估系统，以确定听众对演讲者的看法。语音的自动评估已经出现在口语能力中，它利用了自动语音识别（ASR）和语义分析。自动语音评估也被用于测谎和情绪检测，它们关注的是用户的自主反应。S的声音，如当压力影响声带。这个SBIR项目背后的假设是，说话者可以有意识地使用和修改非语义言语行为，以产生更理想的听者感知。将听者感知与言语行为自动关联是语音自动评价的新方向。第二阶段的目标是开发足够的软件来自动评估公开演讲，这样学生就可以？S的声音传递可以客观地测量，并以一种创造独立、个性化学习体验的方式呈现。在第一阶段调查的语音分析功能将被增强并发展成基于云的服务，帮助学生练习、跟踪和改善他们的公开演讲习惯。

This Phase II project aims to develop software to automatically assess public speaking skills and prepare students with better oral communications skills necessary to perform job tasks. Oral expression is the most highly valued ability throughout the economy and ranks as the second most highly-valued skill for high-wage, high-growth, high-skill occupations. Approximately 4.5 million college students take a basic communications course each year, however, as class sizes get larger and online learning becomes more common, public speaking instruction becomes increasingly difficult. Practice and feedback are essential aspects of these courses, yet it is a struggle for teachers to find enough time to sufficiently interact with students. This SBIR project aims to develop the key concepts of automated public speaking assessment such that a student?s vocal delivery can be objectively measured and presented in a manner that creates an independent, personalized learning experience. Unlike traditional methods of public speaking assessment, the proposed system can be available at any time, provide objective feedback and track student practice and improvement. The proposed Software-as-a-Service is projected to generate $16 Million in revenue over five years and create more than 25 high-paying, US-based jobs. This Small Business Innovative Research (SBIR) Phase II project proposes to develop an automated assessment system for public speaking that determines how a speaker would be perceived by an audience. Automated assessment for speech has already occurred in spoken language proficiency, which leverages Automated Speech Recognition (ASR) and semantic analysis. Automated voice assessment has also been utilized in lie detection and emotion detection, which focus on autonomic responses in the user?s voice, such as when stress affects the vocal cords. The hypothesis behind this SBIR project is that speakers can consciously use and modify non-semantic speech behaviors to produce more desirable listener perceptions. Automatically linking listener perception to speech behaviors represents a novel direction in automated assessment for speech. The Phase II objective is to develop software sufficient for automated public speaking assessment such that a student?s vocal delivery can be objectively measured and presented in a manner that creates an independent, personalized learning experience. Voice analytics capability investigated in Phase I will be enhanced and developed into a cloud-based service which helps students practice, track, and improve their public speaking habits.