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首页> 外文会议>International conference on natural language and speech processing >Automatic Data-Driven Approaches for Evaluating the Phonemic Verbal Fluency Task with Healthy Adults
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Automatic Data-Driven Approaches for Evaluating the Phonemic Verbal Fluency Task with Healthy Adults

机译：自动数据驱动方法来评估健康成年人的语音口语流利度任务

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摘要

Phonemic Verbal Fluency (PVF) is a cognitive assessment task where a patient is asked to produce words constrained to a given alphabetical letter for a specified time duration. Patient productions are later evaluated based on strategies to reveal crucial diagnostic information by manually scoring results according to predetermined clinical criteria. In this paper, we propose four alternative similarity metrics and evaluate them in a two-fold argument, using the clinical criteria as a baseline. First, we consider the capacity of each metric to model PVF production using a rank-based approach, and then consider the metrics ability to compute finer resolution clinical measures that are indicative of the underlying strategy. Automation of the clinical criteria and proposed metrics are evaluated on PVF performances for 16 letters from 32 healthy German students (n=512). Weighted phonemic edit distance performed best overall for modelling both production and strategy.
机译：语音口语流利性（PVF）是一项认知评估任务，要求患者在指定的持续时间内产生受限于给定字母的单词。后来根据策略根据预定的临床标准对结果进行人工评分，对患者的病情进行评估，以显示关键的诊断信息。在本文中，我们提出了四个替代的相似性指标，并以临床标准为基准，以两个角度对它们进行了评估。首先，我们考虑使用基于等级的方法对每个指标进行PVF生产建模的能力，然后考虑指标能力以计算更精细的临床指标，这些指标指示了基本策略。对来自32名健康德国学生（n = 512）的16个字母的PVF表现进行临床标准和建议指标的自动化评估。加权音位编辑距离在制作产品和策略时总体表现最佳。

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