DETECTION OF FILLERS IN THE SPEECH BY PEOPLE WHO STUTTER

Q3 Economics, Econometrics and Finance
Waldemar Suszynski, M. Charytanowicz, Wojciech Rosa, L. Koczan, R. Stegierski
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引用次数: 0

Abstract

Stuttering is a speech impediment that is a very complex disorder. It is difficult to diagnose and treat, and is of unknown initiation, despite the large number of studies in this field. Stuttering can take many forms and varies from person to person, and it can change under the influence of external factors. Diagnosing and treating speech disorders such as stuttering requires from a speech therapist, not only good profes-sional preparation, but also experience gained through research and practice in the field. The use of acoustic methods in combination with elements of artificial intelligence makes it possible to objectively assess the disorder, as well as to control the effects of treatment. The main aim of the study was to present an algorithm for automatic recognition of fillers disfluency in the statements of people who stutter. This is done on the basis of their parameterized features in the amplitude-frequency space. The work provides as well, exemplary results demonstrating their possibility and effectiveness. In order to verify and optimize the procedures, the statements of seven stutterers with duration of 2 to 4 minutes were selected. Over 70% efficiency and predictability of automatic detection of these disfluencies was achieved. The use of an automatic method in conjunction with therapy for a stuttering person can give us the opportunity to objectively assess the disorder, as well as to evaluate the progress of therapy.
口吃者对言语中的填充物的检测
口吃是一种非常复杂的言语障碍。尽管在该领域进行了大量研究,但它很难诊断和治疗,而且起源不明。口吃有多种形式,因人而异,而且在外部因素的影响下会发生变化。诊断和治疗口吃等言语障碍不仅需要言语治疗师做好专业准备,还需要通过该领域的研究和实践获得经验。声学方法与人工智能元素相结合的使用使客观评估疾病以及控制治疗效果成为可能。这项研究的主要目的是提出一种自动识别口吃者陈述中填充词不流畅的算法。这是基于它们在幅频空间中的参数化特征来完成的。这项工作也提供了示范性的结果,证明了它们的可能性和有效性。为了验证和优化程序,选择了7名持续时间为2-4分钟的口吃者的陈述。实现了70%以上的效率和可预测性的自动检测这些障碍。将自动方法与口吃患者的治疗相结合,可以让我们有机会客观评估这种障碍,并评估治疗的进展。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Applied Computer Science
Applied Computer Science Engineering-Industrial and Manufacturing Engineering
CiteScore
1.50
自引率
0.00%
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0
审稿时长
8 weeks
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