A psychoacoustic approach to dysphonic voice quality perception

描述（由申请人提供）：语音障碍通常会导致患者、临床医生和谈话伙伴注意到的语音质量变化，语音质量的改善是治疗的关键结果。然而，我们对人们如何感知语音质量的了解有限。这限制了我们准确量化或描述质量变化的能力，例如由于疾病或治疗引起的变化。这个延续项目结合了声音科学，言语科学，听力科学和工程学的概念和技术来解决这个问题。一般来说，研究首先在实验室中获得高精度的语音质量感知测量。然后，这些数据用于开发准确反映听众数据的语音质量感知的数学模型。为了获得人对语音质量的判断与模型输出之间的紧密匹配，使用听觉处理模型来获得语音声学信号的内部表示。然后，从该内部听觉表示中捕获特定的测量，并用于对语音质量的感知进行建模。方法获得知觉判断的单一语音质量维度，声学信号的转换，其内部表示，和语音质量模型的一般形式已经完成了两个不同的语音质量维度（呼吸和粗糙度）使用简单的刺激（元音/a/在“热”）。在拟议的工作中，这些方法将进一步发展，以建立一个框架，全面了解语音质量感知，并使翻译到临床实践。这些方法将（1）用于解释多个共同出现的语音质量维度;（2）应用于更自然和复杂的刺激（多个元音和音节）;（3）用于理解其他语音质量维度（应变）。(4)为了提高模型的准确性，并扩大其适用性，以严重的发音困难的声音（如第二类和第三类），方法来估计“音高”和“音高强度”的发音困难的声音将开发和纳入相关的模型。(4)为了以提高临床实用性的方式增强测量方案，模型输出将被转换为直观地与每个语音质量维度的感知幅度相关的尺度。这将创建一组直观的语音质量指标，易于使用和解释。(5)最后，将通过初步临床研究评估在常规临床评估中使用这些模型和指标的可行性。

DESCRIPTION (provided by applicant): Voice disorders often lead to changes in voice quality noticed by patients, clinicians, and conversation partners, and improvement in voice quality is a critical outcome of treatment. However, we have limited knowledge of how people perceive voice quality. This has restricted our ability to accurately quantify or describe changes in qualit, such as due to a disease or when resulting from treatment. This continuation project combines concepts and techniques from voice science, speech science, hearing science, and engineering to address this problem. In general, the research proceeds by first obtaining high-precision measures of voice quality perception in the laboratory. These data are then used to develop mathematical models of voice quality perception that accurately reflect listeners' data. To obtain a close match between human judgments of voice quality and model output, models of auditory processing are used to obtain an internal representation of the voice acoustic signal. Specific measures are then captured from this internal auditory representation and used to model the perception of voice quality. Methods for obtaining perceptual judgments of single voice quality dimensions, the transformation of the acoustic signal to its internal representation, and the general form of the voice quality models have been completed for two different voice quality dimensions (breathiness and roughness) using simple stimuli (vowel /a/ as in "hot"). In the proposed work, these approaches will be developed further to establish a framework for comprehensive understanding of voice quality perception and to enable translation to clinical practice. These approaches will be (1) used to account for multiple, co-occurring voice quality dimensions; (2) applied to more natural and complex stimuli (multiple vowels and syllables); and (3) leveraged to understand other voice quality dimensions (strain). (4) To increase model accuracy and to expand their applicability to severely dysphonic voices (e.g. Type II and Type III), methods to estimate the "pitch" and "pitch strength" of dysphonic voices will be developed and incorporated into relevant models. (4) To enhance the measurement schemes in a manner that improves clinical utility, model output will be transformed to a scale that is intuitively relted to the perceptual magnitude of each voice quality dimension. This will create a set of intuitive voice quality metrics that are easy to use and interpret. (5) Finally, the feasibility of using thee models and metrics in regular clinical assessment will be evaluated through an initial clinical study.