亨廷顿舞蹈症的声学和词汇特征分类
Classification of Huntington Disease using Acoustic and Lexical Features
摘要：
言语是亨廷顿舞蹈症（HD）的重要生物标志物，随着疾病的进展，言语的变化严重程度增加。语音分析目前使用由受过训练的专业人员手动创建的transmittance或使用全球评级量表进行。人工转录既昂贵又耗时，全球评级量表可能缺乏足够的敏感性和保真度。最终，我们需要的是一种不引人注目的措施，可以廉价和持续地跟踪疾病的进展。我们目前的第一个步骤，这样一个系统的发展，展示了能够自动区分健康的控制和个人与HD使用语音提示。结果提供的证据表明，客观分析可用于支持临床诊断，朝着实验室和临床环境之外的跟踪发展。
英文摘要：
Speech is a critical biomarker for Huntington Disease (HD), with changes in speech increasing in severity as the disease progresses. Speech analyses are currently conducted using either transcriptions created manually by trained professionals or using global rating scales. Manual transcription is both expensive and time-consuming and global rating scales may lack sufficient sensitivity and fidelity. Ultimately, what is needed is an unobtrusive measure that can cheaply and continuously track disease progression. We present first steps towards the development of such a system, demonstrating the ability to automatically differentiate between healthy controls and individuals with HD using speech cues. The results provide evidence that objective analyses can be used to support clinical diagnoses, moving towards the tracking of symptomatology outside of laboratory and clinical environments.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
