AUTOMATIC ANALYSIS AND DIAGNOSIS OF DYSARTHRIA

构音障碍亚型的鉴别诊断很重要，因为它使临床医生能够确定疾病的病变位置，并允许临床医生和患者制定适当的治疗目标。更重要的是一种可靠、客观的方法来记录治疗效果。知觉评估构音障碍的方法是最常见的。然而，专家之间的差异比诊断或监测所需的差异更大，而且很难量化。我们提出一个自动声学特征识别系统，以帮助临床医生评估构音障碍。该系统和两名语音学家将接受训练，从各种构音障碍患者所说的持续元音和重音动音节中判断声学特征。该系统将根据声门脉冲的周期性或双声动力学音节的频率和规律性等声学特征进行判断。语音学家会根据感知特征做出判断，比如呼吸、复音、刺耳、刺耳等。第一阶段的目标是表明所提出的系统能够以90%的准确率识别构音障碍不同亚型的声学特征，相对于人类对相关感知特征的判断。很明显，需要一种有效、可靠和客观的工具来评估语言障碍个体的语言。该软件可以与现有的声学分析系统捆绑在一起，这些系统目前被医院、诊所和大学购买，用于非自动分析困难语音。

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.