AUTOMATIC ANALYSIS AND DIAGNOSIS OF DYSARTHRIA

构音障碍的自动分析与诊断

• 批准号: 6016961
• 负责人: KAREN V CHENAUSKY
• 金额: $ 10.13万
• 依托单位: SPEECH TECHNOLOGY/APPLIED RESEARCH CORP.
• 依托单位国家: 美国
• 财政年份: 1999
• 资助国家: 美国
• 起止时间: 1999-09-30 至 2000-09-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/6016961
• 关键词: biomedical automation; clinical research; computer assisted diagnosis; computer program /software; computer system design /evaluation; diagnosis design /evaluation; dysarthria; human subject; human therapy evaluation; phonology; psychoacoustics; speech disorder diagnosis; speech recognition; biomedical automation; clinical research; computer assisted diagnosis; computer program /software; computer system design /evaluation; diagnosis design /evaluation; dysarthria; human subject; human therapy evaluation; phonology; psychoacoustics; speech disorder diagnosis; speech recognition

Differential diagnosis of subtypes of dysarthria is important because it enables clinicians to determine the location of the lesion responsible for the disorder and allows clinician and patient to set appropriate treatment goals. Even more important is a reliable, objective method of documenting treatment efficacy. Perceptual methods of evaluating dysarthria are most common. Yet differences between experts are larger than the differences needed for diagnosis or monitoring and are hard to quantify. We propose an automatic acoustic-feature recognition system to aid clinicians in evaluating dysarthria. The system and two phoneticians will be trained to judge acoustic features from sustained vowels and diadochokinetic syllables spoke by subjects with a variety of dysarthrias. The system will make its judgement from acoustic features like periodicity of glottal pulses or rate and regularity of diadochokinetic syllables, and others. The phoneticians will make their judgements based on perceptual features like breathiness, diplophonia, harshness, harshness, and others. The goal of Phase I is to show that the proposed system can identify the acoustic characteristics of different subtypes of dysarthria at 90 percent accuracy with respect to human judgements of the associated perceptual features. PROPOSED COMMERCIAL APPLICATION There is a clear need for an efficient, reliable, and objective tool to evaluate the speech of dysarthric individuals. The software could be packaged with existing acoustic analysis systems which are currently purchased by hospitals, clinics, and universities for non-automatic analysis of dysarthric speech.

对构音障碍亚型的差异诊断很重要，因为它使临床医生能够确定负责该疾病的病变的位置，并允许临床医生和患者设定适当的治疗目标。 更重要的是记录治疗功效的可靠，客观的方法。 评估构音障碍的感知方法是最常见的。 然而，专家之间的差异大于诊断或监测所需的差异，并且很难量化。 我们提出了一个自动的声学识别系统，以帮助临床医生评估构音障碍。 该系统和两名语音家将接受培训，以判断持续的元音和多种构造障碍的受试者的声音特征。 该系统将从声学特征等声学特征做出判断，例如震颤脉冲的周期性或diadiochokinetic音节等的速率和规律性。 语音家将根据呼吸，外交，苛刻，苛刻等的感知特征做出判断。 第一阶段的目的是表明，提出的系统可以在人类对相关感知特征的判断方面，以90％的精度确定不同亚型的构音障碍的声学特征。拟议的商业应用显然需要有效，可靠和客观的工具来评估违反障碍个体的言论。 该软件可以包装在现有的声学分析系统中，这些系统目前由医院，诊所和大学购买，以进行违反语音的非自动分析。