Lexical Diversity and Language Impairment

Natalia Časnochová Zozuk
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Abstract

Abstract The development of artificial intelligence tools has seen an enormous growth recently. Linguistic artificial intelligence tools are being successfully applied in the field of speech analysis and discourse. In our study, we used automatic NLP tools to detect differences in picture description in the discourse of people diagnosed with Alzheimer’s disease (AD), Mild Cognitive Impairment (MCI) and healthy people. A measure of lexical diversity was used to compare discourse complexity. Transcripts of recordings of the probands within the EWA project were used in the study. From the multiple comparisons, we found that there is a statistically significant difference between healthy people and people suffering from MCI and AD. Our results indicate that healthy people have more lexical diversity than people suffering from MCI and AD – a more diverse vocabulary in spontaneous speech, in our case, when describing a picture.
词汇多样性与语言障碍
摘要 人工智能工具的发展近来出现了巨大的增长。语言人工智能工具已成功应用于语音分析和话语领域。在我们的研究中,我们使用自动 NLP 工具来检测阿尔茨海默病(AD)患者、轻度认知障碍患者(MCI)和健康人话语中图片说明的差异。为了比较话语的复杂性,我们使用了词汇多样性的测量方法。本研究使用了 EWA 项目中受试者的录音记录。通过多重比较,我们发现健康人与 MCI 和 AD 患者之间存在显著的统计学差异。我们的研究结果表明,健康人比 MCI 和 AD 患者拥有更多的词汇多样性--在自发言语中,在我们的案例中,在描述一幅图片时,健康人拥有更多的词汇多样性。
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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