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Towards a speech therapy support system based on phonological processes early detection

机译：朝着基于语音过程的语音治疗支持系统早期检测

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摘要

Phonological disorders are characterized by substitutions, insertion and/or deletions of sounds during the process of language acquisition, which are known as Phonological Processes (PPs). In the speech therapy domain, an early identification of PPs allows the diagnosis and treatment of various pathologies and may improve clinical tasks, however, there are few proposals that focus on the identification of PPs for supporting Speech-Language Pathologists (SLPs). Recent research applied Case-Based Reasoning (CBR) in medical domain to identify specific cases related to patients. Situation-Awareness (SA) is a technique that allows computing systems to adapt itself and respond to users or other systems according to environment information. Moreover, there is no indicative in related literature of CBR and SA being used for detecting PPs that may occur in pronunciation. In this paper, we introduce the union of SA and CBR, tied to machine learning algorithms for proposing a system to predict PPs, supporting specialists in their clinical decisions. To evaluate the system, we implemented it in a software architecture prototype and evaluated the prototypes using a knowledge base containing near one hundred thousand audio files, collected from more than 1,000 pronunciation assessments. The evaluation of the prototypes showed an accuracy over 93% in the prediction of PPs, resulting in a efficient tool for clinical decision support and therapeutic planning. We also presented a direct qualitative comparison between our approach and related work.
机译：语音紊乱的特征在于语言采集过程中的声音，插入和/或缺失，称为语音过程（PPS）。在语音治疗域中，PPS的早期鉴定允许诊断和治疗各种病理学，并且可以改善临床任务，但是，很少有专注于支持语音语言病理学家（SLP）的PPS的识别。最近的研究应用案例的理解（CBR）在医学领域识别与患者有关的特定病例。情况感知（SA）是一种技术，允许计算系统根据环境信息对用户或其他系统进行调整和响应用户或其他系统。此外，CBR的相关文献中没有指示用于检测可能发生的PPS的CBR和SA。在本文中，我们介绍了SA和CBR的联盟，与机器学习算法相关联，以提出一个系统预测PPS，支持他们的临床决策。为了评估系统，我们在软件架构原型中实现了它，并使用从超过1,000个发音评估收集的包含近十万个音频文件的知识库进行评估原型。原型的评估在预测PPS的预测中显示出超过93％的精度，导致临床决策支持和治疗规划的有效工具。我们还在我们的方法与相关工作之间提供了直接的定性比较。

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