The effects of telepractice technology on dysarthric speech evaluation

项目摘要/摘要 随着远程实践成为诊所就诊的一种日益流行的、甚至是必要的替代方案，演讲- 语言病理学家(SLP)评估通过音频捕获并远程传输的语音 电话会议解决方案(如Zoom)。所有流行的电话会议应用程序都使用语音压缩 基于线性预测编码(LPC)的算法，以减少语音传输所需的带宽。LPC 压缩算法将语音分解为发音源和发音过滤器参数，它们是 然后基于已经开发的方案独立地进行矢量量化和时间平滑 并且被优化用于压缩从普通人群中采样的语音。通过这种方式，语音被传输 对于给定的互联网连接，具有最少数量的可听伪像和最高级别的可理解性 约束条件。由于LPC算法是使用典型语音的大型语料库进行优化的，因此它们是 从根本上不适合于忠实地传输通常存在于 构音障碍的语音信号以及发音和声音特征特别容易受到损坏。在这 提案的目的是系统地表征语音压缩算法的影响 用于语音清晰度、感知评估和声学测量的远程实践平台。这 是通过两个目标实现的： SA1：评估电话会议语音压缩算法在三个互联网上的效果 构音障碍言语知觉和声学评价中的带宽水平 现有的高保真单词和句子录音，以及来自20位演讲者的持续发音 各种构音障碍将以三种压缩速率进行编码，以模拟低、中、高... 带宽互联网连接。20个SLP将转录样本以获得可理解性测量 原创和编码的单词和句子；并根据持续的发音对声音质量进行感知评级。 清晰度和声音的声学测量将被提取。受试者内部统计模型将评估 在语音任务中，带宽状况对知觉和听觉结果的影响。 SA2：比较在远程练习会议中记录的构音障碍的结果(压缩)与 通过智能手机应用程序(未压缩)面对面同步录制的视频。 15名有构音障碍的演讲者将参加由 SLPS。随后，来自会议的录音(压缩)和同时录制的亲自样本 (未压缩)将由SLP评分。面对面录制也将像在SA1条件下一样被压缩。 声学指标将从所有样本中提取。受试者内部的统计模型将评估样本 不同条件下的差异(未压缩、在远程练习期间压缩、低-中-和高- 带宽压缩级别)。结果将告知远程实践对构音障碍评估的限度。

Project Summary/Abstract With telepractice becoming an increasingly popular, indeed necessary, alternative to clinic visits, speech- language pathologists (SLPs) evaluate speech that is audio captured and transmitted remotely via a teleconferencing solutions (e.g. Zoom). All popular teleconferencing applications use speech compression algorithms based on linear predictive coding (LPC) to reduce bandwidth required for speech transmission. LPC compression algorithms decompose speech into phonatory source and articulatory filter parameters, which are then independently vector quantized and temporally smoothed based on schemes that have been developed and optimized for compressing speech sampled from the general population. In this way, speech is transmitted with the least number of audible artifacts and the highest level of intelligibility for the given internet connection constraints. Because LPC algorithms are optimized using large corpora of typical speech, they are fundamentally not well-suited for faithfully transmitting the amount of distortion or noise commonly present in the dysarthric speech signal, and articulation and voice features are particularly vulnerable to corruption. In this proposal the aim is to systematically characterize the impact of speech compression algorithms commonly used in telepractice platforms on speech intelligibility, perceptual evaluation, and acoustic measurement. This is done via two aims: SA1: Evaluate the effects of teleconferencing speech compression algorithms at three internet bandwidth levels on the perceptual and acoustic assessment of dysarthric speech Existing high-fidelity audio recordings of words and sentences and sustained phonations from 20 speakers with various dysarthrias will be encoded at three compression rates to simulate low-, moderate-, and high- bandwidth internet connectivity. Twenty SLPs will transcribe the samples to attain intelligibility measures for the original and encoded words and sentences; and perceptually rate vocal quality on sustained phonations. Acoustic measures of articulation and voice will be extracted. Within-subject statistical models will evaluate impact of bandwidth condition on perceptual and acoustic outcomes within speech tasks. SA2: Compare outcomes for dysarthric speech recorded in a telepractice session (compressed) versus that recorded simultaneously in-person via smartphone application (uncompressed). Fifteen speakers with dysarthria will participate in simulated telepractice speech assessments administered by SLPs. Subsequently, recordings from session (compressed) and simultaneously recorded in-person samples (uncompressed) will be scored by SLPs. In-person recordings will also be compressed as in SA1 conditions. Acoustic metrics will be extracted from all samples. Within-subject statistical models will evaluate sample differences across conditions (uncompressed, compressed during telepractice, and low- moderate- and high- bandwidth compression levels). Results will inform the limits of telepractice for dysarthria evaluation.