LANDMARK ANALYSIS OF DYSARTHRIC SPEECH

构音障碍言语的标志性分析

• 批准号: 6214424
• 负责人: KAREN V CHENAUSKY
• 金额: $ 12.6万
• 依托单位: SPEECH TECHNOLOGY/APPLIED RESEARCH CORP.
• 依托单位国家: 美国
• 财政年份: 2000
• 资助国家: 美国
• 起止时间: 2000-09-15 至 2001-07-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/6214424
• 关键词: assistive device /technology; clinical research; computer human interaction; computer program /software; computer system design /evaluation; dysarthria; human subject; speech recognition; vocabulary

The speech of individuals with dysarthria is highly variable and causes even trained, speaker-dependent speech recognizers to fail to recognize dysarthric speech. A novel method is proposed for recognizing words from a very small vocabulary of dysarthric speech. The method uses a "landmark"-based classifier (LMC) to identify sequences of acoustic events in speech. This new method does not depend on a stored database of speech. For small word sets, each landmark series will correspond to a unique word or phrase; the numbers from 1-20 and from 20-100 by tens form such a set. Small vocabularies are useful for applications such as speech interfaces for remote telephone and appliance control. Remote control systems are useful for motorically individuals and increase independence and safety. This project will extend the result for numbers spoken by normal subjects to more words and to some moderate dysarthrics. It will also determine whether these landmark series can be detected automatically in dysarthric speech by an LMC. If they can be detected robustly, Phase II will extend the analyses to a wider variety of dysarthric speech and a larger vocabulary, appropriate for remote control. PROPOSED COMMERCIAL APPLICATION: There is a clear need for speech recognition technology that will recognize disordered speech. The software could be used as a hands-free interface for AAC devices or environmental controllers.

构造障碍的人的言论高度可变，甚至导致训练，依赖说话者的语音识别者无法识别违反违规言语。 提出了一种新的方法，以识别命运障碍词汇量很小的单词。该方法使用基于“地标”的分类器（LMC）来识别语音中的声学事件序列。这种新方法不取决于存储的语音数据库。对于小单词集，每个具有里程碑意义的系列将对应于一个唯一的单词或短语。从1-20到20-100的数字，由TENS形成这样的组合。小词汇对于诸如远程电话和设备控制的语音接口等应用很有用。遥控系统对志愿个人有用，并提高独立性和安全性。该项目将将正常受试者说的数字扩展到更多单词和一些中等障碍的结果。它还将确定是否可以在LMC中自动检测这些里程标系列。如果可以强遵守它们，那么第二阶段将把分析扩展到更广泛的违反语音和更大的词汇量，适合遥控。拟议的商业应用：显然需要语音识别技术，该技术将识别言语无序。该软件可以用作AAC设备或环境控制器的免提接口。