SBIR Phase I: Say What I Feel

这个SBIR第一阶段项目旨在创建一个基于软件的情感表达语音生成通信系统，该系统专为语言交流能力很低或没有语言交流能力的个人设计--特别是那些患有自闭症谱系障碍的人。当前的替代交流技术不具备表达情感内容的能力，而情感内容对于家庭、社区和工作中的有效、可理解的交流至关重要。通过语气或面部表情表达情绪--例如悲伤、愤怒或快乐--的能力，对有沟通困难的人来说，具有深远的教育和职业益处。换句话说，情绪化内容有助于阐明口语信息背后的交际意图。当非语言个体能够进行彻底和有效的交流时，他们就会提高接受免费和适当的公共教育的能力，并扩大他们的职业机会。当个人能够接受教育并找到工作时，他们就可以回馈社会。拟议的工作支持科学和工程方面的进步，但它也增强了当前教育应用和未来研究的潜力。最后，该项目以联邦和州政府为残疾人提供教育和职业服务的努力为基础。该项目将开发和结合针对数字面部识别模式和基于语音的波形的新型软件算法，以增强无法随意说话的个人对话交流的情感内容。将情感内容添加到合成语音中的能力是一项新技术，可以极大地造福于有沟通困难的个人，例如患有自闭症谱系障碍的人。该项目旨在促进和增强情感表达，从而提高使用基于软件的合成语音系统来表达他们的想法、感觉和愿望的个人的交流能力。衡量这个项目是否准确地在语音和面部表情中传达人类情感，需要进行一项涉及神经典型成年人的知觉测试。具体地说，知觉测试将包括受过培训和未受过培训的法官。这样做的目的是确保面部表情以及音调轮廓和声音强调与情感标签(即，快乐、悲伤或疯狂)对齐。为了准确计算评委之间的可信度，这项研究将使用一种方法来确定评委的评分与他们可能在多大程度上符合的程度，如果他们随机对相同的刺激进行评分。

This SBIR Phase I project aims to create an emotionally expressive software-based speech-generating communication system, which is designed for individuals with little or no verbal communication ability -- particularly those with autism spectrum disorder. Current alternative communication technology does not offer the ability to express emotional content: something that is crucial to effective, comprehensible communication at home, in the community, and at work. The ability to convey emotions -- sadness, anger, or happiness, for example -- through one's tone of voice or facial expressions has far-reaching educational and vocational benefits for individuals with communication challenges. In other words, emotional content helps clarify the communicative intent behind a spoken message. When non-verbal individuals can communicate thoroughly and effectively, they increase their ability to receive a free and appropriate public education, and they expand their vocational opportunities. When individuals can receive an education and find a job, they can contribute back to society. The proposed work supports progress in science and engineering, yet it also enhances the potential for current educational applications and future research studies. Finally, this project builds on Federal and State efforts to offer people with disabilities educational and vocational services. This project will develop and combine novel software algorithms that target digital facial recognition patterns and speech-based waveforms, in order to enhance the emotional content of conversational communication for individuals who cannot speak volitionally. The ability to add emotional content onto synthesized speech is a new technology that could substantially benefit individuals with communication challenges, such as people with autism spectrum disorder. This project seeks to facilitate and augment emotional expression and, therefore, increase communicative competence for individuals who use software-based synthesized speech systems to express their ideas, feelings, and wishes. Measuring whether or not this project accurately conveys human emotion in speech and facial expressions requires a perceptual test involving neurotypical adults. Specifically, the perceptual test will include both trained and untrained judges. The purpose of this is to ensure that the facial expressions as well as the pitch contour and vocal emphasis align with the emotion labels (i.e., happy, sad, or mad). In order to accurately calculate the judges' inter-rater reliability, the study will use a method that determines the extent to which judges' ratings agree, relative to how much they would likely conform, if they were to randomly rate the same stimuli.