Purpose Apraxia of speech (AOS) is a consequence of stroke that frequently co-occurs with aphasia. Its study is limited by difficulties with its perceptual evaluation and dissociation from co-occurring impairments. This study examined the classification accuracy of several acoustic measures for the differential diagnosis of AOS in a sample of stroke survivors. Method Fifty-seven individuals were included (mean age = 60.8 ± 10.4 years; 21 women, 36 men; mean months poststroke = 54.7 ± 46). Participants were grouped on the basis of speech/language testing as follows: AOS-Aphasia (n = 20), Aphasia Only (n = 24), and Stroke Control (n = 13). Normalized Pairwise Variability Index, proportion of distortion errors, voice onset time variability, and amplitude envelope modulation spectrum variables were obtained from connected speech samples. Measures were analyzed for group differences and entered into a linear discriminant analysis to predict diagnostic classification. Results Out-of-sample classification accuracy of all measures was over 90%. The envelope modulation spectrum variables had the greatest impact on classification when all measures were analyzed together. Conclusions This study contributes to efforts to identify objective acoustic measures that can facilitate the differential diagnosis of AOS. Results suggest that further study of these measures is warranted to determine the best predictors of AOS diagnosis. Supplemental Materials https://doi.org/10.23641/asha.5611309.

中文翻译：

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语音失用症鉴别诊断的多元分析方法。

目的言语失用症（AOS）是中风经常与失语症并发的结果。它的研究受到其感知评估的困难以及与共现障碍的分离的限制。这项研究检查了中风幸存者样本中用于鉴别AOS的几种声学方法的分类准确性。方法包括57名个体（平均年龄= 60.8±10.4岁； 21名女性，36名男性；中风后平均月数= 54.7±46）。根据语音/语言测试，将参加者分组如下：AOS-失语症（n = 20），仅失语症（n = 24）和中风控制（n = 13）。从连接的语音样本中获取归一化的成对变异性指数，失真误差的比例，语音开始时间变异性和幅度包络调制频谱变量。对组差异进行分析，并进行线性判别分析以预测诊断分类。结果所有指标的样本外分类准确率均超过90％。当一起分析所有度量时，包络调制频谱变量对分类的影响最大。结论本研究有助于确定客观的声学措施，以促进AOS的鉴别诊断。结果表明，有必要进一步研究这些措施，以确定AOS诊断的最佳预测指标。补充材料https://doi.org/10.23641/asha.5611309。当一起分析所有度量时，包络调制频谱变量对分类的影响最大。结论本研究有助于确定客观的声学措施，以促进AOS的鉴别诊断。结果表明，有必要进一步研究这些措施，以确定AOS诊断的最佳预测指标。补充材料https://doi.org/10.23641/asha.5611309。当一起分析所有度量时，包络调制频谱变量对分类的影响最大。结论本研究有助于确定客观的声学措施，以促进AOS的鉴别诊断。结果表明，有必要进一步研究这些措施，以确定AOS诊断的最佳预测指标。补充材料https://doi.org/10.23641/asha.5611309。