Ballard Kirrie J, Etter Nicole M, Shen Songjia, Monroe Penelope, Tien Tan Chek
Faculty of Health Sciences, University of Sydney, New South Wales, Australia.
Department of Communication Sciences and Disorders, Pennsylvania State University, University Park.
Am J Speech Lang Pathol. 2019 Jul 15;28(2S):818-834. doi: 10.1044/2018_AJSLP-MSC18-18-0109.
Purpose Individuals with neurogenic speech disorders require ongoing therapeutic support to achieve functional communication goals. Alternative methods for service delivery, such as tablet-based speech therapy applications, may help bridge the gap and bring therapeutic interventions to the patient in an engaging way. The purpose of this study was to evaluate an iPad-based speech therapy app that uses automatic speech recognition (ASR) software to provide feedback on speech accuracy to determine the ASR's accuracy against human judgment and whether participants' speech improved with this ASR-based feedback. Method Five participants with apraxia of speech plus aphasia secondary to stroke completed an intensive 4-week at-home therapy program using a novel word training app with built-in ASR. Multiple baselines across participants and behaviors designs were employed, with weekly probes and follow-up at 1 month posttreatment. Four sessions a week of 100 practice trials each were prescribed, with 1 being clinician-run and the remainder done independently. Dependent variables of interest were ASR-human agreement on accuracy during practice trials and human-judged word production accuracy over time in probes. Also, user experience surveys were completed immediately posttreatment. Results ASR-human agreement on accuracy averaged ~80%, which is a common threshold applied for interrater agreement. All participants demonstrated improved word production accuracy over time with the ASR-based feedback and maintenance of gains after 1 month. All participants reported enjoying using the app with support of a speech pathologist. Conclusion For these participants with apraxia of speech plus aphasia due to stroke, satisfactory gains were made in word production accuracy with an app-based therapy program providing ASR-based feedback on accuracy. Findings support further testing of this ASR-based approach as a supplement to clinician-run sessions to assist clients with similar profiles in achieving higher amount and intensity of practice as well as empowering them to manage their own therapy program. Supplemental Material https://doi.org/10.23641/asha.8206628.
目的 患有神经性言语障碍的个体需要持续的治疗支持以实现功能性沟通目标。替代服务提供方法，如基于平板电脑的言语治疗应用程序，可能有助于弥合差距，并以引人入胜的方式为患者带来治疗干预。本研究的目的是评估一款基于iPad的言语治疗应用程序，该应用程序使用自动语音识别（ASR）软件提供语音准确性反馈，以确定ASR相对于人类判断的准确性，以及参与者的语音是否通过这种基于ASR的反馈得到改善。方法 五名因中风导致言语失用症加失语症的参与者使用一款具有内置ASR的新型单词训练应用程序，完成了为期4周的强化在家治疗计划。采用了跨参与者和行为设计的多个基线，每周进行一次探测，并在治疗后1个月进行随访。规定每周进行四次，每次100次练习试验，其中一次由临床医生指导，其余由参与者独立完成。感兴趣的因变量包括练习试验期间ASR与人类在准确性上的一致性，以及探测中随时间推移人类判断的单词生成准确性。此外，在治疗后立即完成了用户体验调查。结果 ASR与人类在准确性上的一致性平均约为80%，这是用于评分者间一致性的常见阈值。所有参与者随着时间的推移，在基于ASR的反馈下，单词生成准确性得到了提高，并且在1个月后保持了进步。所有参与者都报告说，在言语病理学家的支持下，很喜欢使用该应用程序。结论 对于这些因中风导致言语失用症加失语症的参与者，基于应用程序的治疗计划提供基于ASR的准确性反馈，在单词生成准确性方面取得了令人满意的进步。研究结果支持进一步测试这种基于ASR的方法，作为临床医生指导课程的补充，以帮助具有类似情况的客户实现更高的练习量和强度，并使他们能够管理自己的治疗计划。补充材料 https://doi.org/10.23641/asha.8206628 。
