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I-Corps: Smart Speech Perception Feedback for Training and Diagnostics

I-Corps：用于训练和诊断的智能语音感知反馈

基本信息

批准号：
1738164
负责人：
Lynne Bernstein
金额：
$ 5万
依托单位：
George Washington University
依托单位国家：
美国
项目类别：
Standard Grant
财政年份：
2017
资助国家：
美国
起止时间：
2017-04-01 至 2018-09-30
项目状态：
已结题

来源：
https://www.nsf.gov/awardsearch/showAward?AWD_ID=1738164&HistoricalAwards=false
关键词：
Corps Smart Speech Perception Feedback

项目摘要

The broader impact/commercial potential of this I-Corps project is to provide technologies and services based on models of speech signals and human speech perception. These models incorporate a deep understanding of the physical speech stimulus and the perceptual representations that drive speech perception. Technology applications to be explored can break new ground in areas such as: (1) Improving the efficacy of audiological testing; (2) Improving the realism of computer-synthesized voices (3) Providing speech perception training for better understanding of non-native speakers or speakers with neurological disorders; (4) Enhancing multisensory speech perception through training of individuals with audiovisual speech processing deficits such as individuals on the autism spectrum; (5) Developing sensory substitution or augmentation through vibrotactile stimuli; and (6) Improving the quality of older adults? lives through visual speech perception training to ameliorate their declines in perceiving auditory speech in noisy backgrounds.This I-Corps project will investigate commercial applications of technologies and services based on models of multisensory speech signals and human speech perception. Human speech perception can be highly errorful in the presence of noise and/or distortions that originate in the talker, the physical communication channel, and/or the perceiver (e.g., hearing loss). The technology to be explored models how speech perception degrades, and how multisensory stimuli compensate for perceptual errors. For example, this technology supports the characterization of speech perception difficulties using a simple talk-back task in which the perceiver repeats what was just said. In formal laboratory experiments, this technology has been used to improve speech perception training outcomes through improvements in the contingencies between perceptual errors and training feedback. This technology can be used in developing media that are designed to reduce the potential for perceptual errors.

这个I-Corps项目更广泛的影响/商业潜力是提供基于语音信号和人类语音感知模型的技术和服务。这些模型结合了对物理语音刺激和驱动语音感知的感知表征的深刻理解。有待探索的技术应用可在以下领域开辟新天地：（1）提高听力测试的功效;（2）提高计算机合成声音的真实性;（3）提供言语感知训练，以便更好地理解非母语人士或患有神经障碍的人士;（4）通过训练具有视听言语处理缺陷的个体（例如自闭症谱系的个体）来增强多感官言语感知;（5）通过振动触觉刺激发展感觉替代或增强;（6）提高老年人的素质？通过视觉语音感知训练来改善他们在嘈杂背景下感知听觉语音的下降。这个I-Corps项目将研究基于多感官语音信号和人类语音感知模型的技术和服务的商业应用。在存在源自讲话者、物理通信信道和/或感知者（例如，听力损失）。待探索的技术模拟语音感知如何退化，以及多感官刺激如何补偿感知错误。例如，该技术支持使用简单的对讲任务来表征语音感知困难，在该任务中，感知者重复刚刚说过的话。在正式的实验室实验中，该技术已被用于通过改善感知错误和训练反馈之间的偶然性来改善语音感知训练结果。这项技术可以用于开发旨在减少感知错误的媒体。