Division of Speech and Hearing Sciences, University of North Carolina at Chapel Hill.
Department of Neurology, University of California San Francisco.
J Speech Lang Hear Res. 2021 Mar 17;64(3):754-775. doi: 10.1044/2020_JSLHR-20-00445. Epub 2021 Feb 25.
Purpose Of the three currently recognized variants of primary progressive aphasia, behavioral differentiation between the nonfluent/agrammatic (nfvPPA) and logopenic (lvPPA) variants is particularly difficult. The challenge includes uncertainty regarding diagnosis of apraxia of speech, which is subsumed within criteria for variant classification. The purpose of this study was to determine the extent to which a variety of speech articulation and prosody metrics for apraxia of speech differentiate between nfvPPA and lvPPA across diverse speech samples. Method The study involved 25 participants with progressive aphasia (10 with nfvPPA, 10 with lvPPA, and five with the semantic variant). Speech samples included a word repetition task, a picture description task, and a story narrative task. We completed acoustic analyses of temporal prosody and quantitative perceptual analyses based on narrow phonetic transcription and then evaluated the degree of differentiation between nfvPPA and lvPPA participants (with the semantic variant serving as a reference point for minimal speech production impairment). Results Most, but not all, articulatory and prosodic metrics differentiated statistically between the nfvPPA and lvPPA groups. Measures of distortion frequency, syllable duration, syllable scanning, and-to a limited extent-syllable stress and phonemic accuracy showed greater impairment in the nfvPPA group. Contrary to expectations, classification was most accurate in connected speech samples. A customized connected speech metric-the narrative syllable duration-yielded excellent to perfect classification accuracy. Discussion Measures of average syllable duration in multisyllabic utterances are useful diagnostic tools for differentiating between nfvPPA and lvPPA, particularly when based on connected speech samples. As such, they are suitable candidates for automatization, large-scale study, and application to clinical practice. The observation that both speech rate and distortion frequency differentiated more effectively in connected speech than on a motor speech examination suggests that it will be important to evaluate interactions between speech and discourse production in future research.
目的
在三种目前公认的原发性进行性失语症变异型中，非流利/语法障碍型（nfvPPA）和失读型（lvPPA）之间的行为差异特别难以区分。这一挑战包括对言语失用症的诊断不确定，后者被归入变异型分类标准。本研究的目的是确定各种言语发音和韵律测量指标在不同言语样本中区分 nfvPPA 和 lvPPA 的程度。
方法
该研究涉及 25 名进行性失语症患者（10 名 nfvPPA、10 名 lvPPA 和 5 名语义变异型）。言语样本包括单词重复任务、图片描述任务和故事叙述任务。我们完成了基于窄音位转录的时间韵律和定量感知分析，并评估了 nfvPPA 和 lvPPA 参与者之间的区分程度（语义变异型作为言语产生损伤最小的参考点）。
结果
大多数（但不是全部）发音和韵律测量指标在 nfvPPA 和 lvPPA 组之间有统计学差异。失真频率、音节时长、音节扫描以及在一定程度上音节重音和音位准确性的测量指标在 nfvPPA 组中表现出更大的损伤。与预期相反，在连贯言语样本中分类最准确。一个定制的连贯言语测量指标——叙述音节时长——产生了极好到完美的分类准确性。
讨论
在多音节言语中平均音节时长的测量指标在区分 nfvPPA 和 lvPPA 方面是有用的诊断工具，尤其是基于连贯言语样本时。因此，它们是自动化、大规模研究以及应用于临床实践的合适候选者。在连贯言语中，言语速度和失真频率的区分比在运动言语检查中更有效，这一观察结果表明，在未来的研究中评估言语和话语产生之间的相互作用将非常重要。
