Perception of dysarthric speech: An objective model of dysarthric speech evaluation with actionable outcomes

项目摘要 语言病理学家训练有素的耳朵是临床评估的黄金标准 练习运动性言语障碍。然而，感性判断很容易受到偏见的影响，他们的 与听者可理解性评估的关系--语言好坏的最终仲裁者--是 不确定。可解释的、客观的和稳健的结果衡量标准，为 迫切需要治疗，以便提供更精确的护理和可靠地监测患者 进步。基于言语感知的理论模型，在我们之前的资助中，我们开发了一种 一组新的结果测量，通过使用提供多维可理解性概况(MIP) 自定义语音刺激和新的编码策略，使我们能够捕获错误类型 听者在听嗓音时会发声。这导致了更完整的可理解性配置文件 这在不同的粒度级别对这些错误进行了编码，从全局到离散。同时，我们 还开发了一种用于评估构音障碍的计算模型，该模型能够可靠地 直接从语音声学估计一组有限的可理解性测量。到目前为止，这两个 结果衡量标准和客观模型仅根据横断面数据进行了评估。在这 续签申请，我们的主要目标是评估有关预期变化的具体假设 作为不同干预指导条件的结果的该多维可理解性简档 (响亮、清晰、缓慢)。该提案的次要目标是进一步完善我们的客观模型以预测 完整的清晰度配置文件并评估其检测清晰度变化的能力 个人演讲者。这对于目前没有客观方法评估其价值的临床医生来说是至关重要的 他们的干预。以通过技术提高护理水平为目标，长期- 这项提案的长期目标是为构音障碍制定独立的客观结果衡量标准，以 为临床医生提供可靠的治疗目标。这样的应用程序有可能戏剧性地 改变目前对神经系统疾病或损伤患者的语言病理学护理标准。 此外，这些应用程序还有可能部分减少健康差距 自动化临床干预，让偏远地区的人更容易获得这些服务 或者在不发达国家。

Project Summary The trained ear of the speech-language pathologist is the gold standard assessment tool for clinical practice in motor speech disorders. However, perceptual judgments are vulnerable to bias and their relationship with estimates of listener intelligibility – the final arbiter of speech goodness – is indeterminate. Interpretable, objective, and robust outcome measures that provide targets for treatment are urgently needed in order to provide more precise care and reliably monitor patient progress. Based on theoretical models of speech perception, in our previous grants we have developed a novel set of outcome measures that provide a multidimensional intelligibility profile (MIP) by using custom speech stimuli and a new coding strategy that allows us to capture the types of errors that listeners make when listening to dysarthric speech. This has led to a more complete intelligibility profile that codifies these errors at different levels of granularity, from global to discrete. Simultaneously, we have also developed a computational model for evaluation of dysarthric speech capable of reliably estimating a limited set of intelligibility measures directly from the speech acoustics. To date, both the outcome measures and the objective model have been evaluated on cross-sectional data only. In this renewal application, our principal goal is to evaluate specific hypotheses regarding expected changes in this multidimensional intelligibility profile as a result of different intervention instruction conditions (loud, clear, slow). A secondary goal of the proposal is to further refine our objective model to predict the complete intelligibility profile and to evaluate its ability to detect intelligibility changes within individual speakers. This is critical for clinicians who currently have no objective ways to assess the value of their interventions. With the aim of improving the standard of care through technology, the long- term goal of this proposal is to develop stand-alone objective outcome measures for dysarthria that can provide clinicians with reliable treatment targets. Such applications have the potential to dramatically alter the current standard of care in speech pathology for patients with neurological disease or injury. Furthermore, these applications also have the potential to reduce health disparities by partially automating clinical intervention and providing easier access to these services to those in remote areas or in underdeveloped countries.