SBIR Phase II: Automated Public Speaking Assessment

这个第二阶段项目旨在开发软件，以自动评估公众演讲技能，并为学生提供更好的口头沟通技能，以完成工作任务。口头表达是整个经济中最受重视的能力，在高工资、高增长、高技能职业中排名第二。每年大约有450万大学生参加基本的沟通课程，然而，随着班级规模越来越大，在线学习变得越来越普遍，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，但教师要找到足够的时间与学生充分互动是一场斗争。这个SBIR项目的目的是发展自动公开演讲评估的关键概念，这样一个学生？的声音传递可以客观地衡量和提出的方式，创造一个独立的，个性化的学习经验。与传统的公开演讲评估方法不同，该系统可以随时提供客观的反馈，并跟踪学生的练习和改进。拟议的软件即服务预计将在五年内产生1600万美元的收入，并创造超过25个高薪的美国工作岗位。这个小企业创新研究（SBIR）第二阶段项目建议开发一个自动评估系统，用于确定演讲者如何被观众感知。 语音的自动评估已经在口语能力中出现，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感检测，重点是在用户的自主反应？的声音，如压力影响声带。这个SBIR项目背后的假设是，说话人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。自动将听者感知与言语行为联系起来是语音自动评价的一个新方向。第二阶段的目标是开发软件足以自动公开演讲评估，使学生？的声音传递可以客观地衡量和提出的方式，创造一个独立的，个性化的学习经验。第一阶段研究的语音分析能力将得到增强，并发展成为一项基于云的服务，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.