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儿童口语中词汇多样性的测量:计算与概念考量

Measurement of Lexical Diversity in Children's Spoken Language: Computational and Conceptual Considerations.

作者信息

Yang Ji Seung, Rosvold Carly, Bernstein Ratner Nan

机构信息

Department of Human Development and Quantitative Methodology, University of Maryland, College Park, College Park, MD, United States.

Department of Hearing and Speech Sciences, Program in Neuroscience and Cognitive Science, College Park, MD, United States.

出版信息

Front Psychol. 2022 Jun 22;13:905789. doi: 10.3389/fpsyg.2022.905789. eCollection 2022.

Abstract

BACKGROUND

Type-Token Ratio (TTR), given its relatively simple hand computation, is one of the few LSA measures calculated by clinicians in everyday practice. However, it has significant well-documented shortcomings; these include instability as a function of sample size, and absence of clear developmental profiles over early childhood. A variety of alternative measures of lexical diversity have been proposed; some, such as Number of Different Words/100 (NDW) can also be computed by hand. However, others, such as Vocabulary Diversity (VocD) and the Moving Average Type Token Ratio (MATTR) rely on complex resampling algorithms that cannot be conducted by hand. To date, no large-scale study of all four measures has evaluated how well any capture typical developmental trends over early childhood, or whether any reliably distinguish typical from atypical profiles of expressive child language ability.

MATERIALS AND METHODS

We conducted linear and non-linear regression analyses for TTR, NDW, VocD, and MATTR scores for samples taken from 946 corpora from typically developing preschool children (ages 2-6 years), engaged in adult-child toy play, from the Child Language Data Exchange System (CHILDES). These were contrasted with 504 samples from children known to have delayed expressive language skills (total = 1,454 samples). We also conducted a separate sub-analysis which examined possible contextual effects of sampling environment on lexical diversity.

RESULTS

Only VocD showed significantly different mean scores between the typically -developing children and delayed developing children group. Using TTR would actually misdiagnose typical children and miss children with known language impairment. However, computation of VocD as a function of toy interactions was significant and emerges as a further caution in use of lexical diversity as a valid proxy index of children's expressive vocabulary skill.

DISCUSSION

This large scale statistical comparison of computer-implemented algorithms for expressive lexical profiles in young children with traditional, hand-calculated measures showed that only VocD met criteria for evidence-based use in LSA. However, VocD was impacted by sample elicitation context, suggesting that non-linguistic factors, such as engagement with elicitation props, contaminate estimates of spoken lexical skill in young children. Implications and suggested directions are discussed.

摘要

背景

词类-形类比(TTR)因其计算相对简单,是临床医生在日常实践中计算的少数几种语言样本分析(LSA)指标之一。然而,它有诸多已被充分记录的显著缺点;这些缺点包括作为样本量函数的不稳定性,以及在幼儿期缺乏清晰的发展轨迹。人们已经提出了各种词汇多样性的替代指标;有些指标,如每100个词中不同词的数量(NDW)也可以手动计算。然而,其他指标,如词汇多样性(VocD)和移动平均词类-形类比(MATTR)则依赖于无法手动进行的复杂重采样算法。迄今为止,尚未有对所有这四种指标的大规模研究评估它们在多大程度上能够捕捉幼儿期典型的发展趋势,或者它们是否能可靠地区分典型与非典型的儿童表达性语言能力特征。

材料与方法

我们对从儿童语言数据交换系统(CHILDES)中抽取的946个来自典型发展的学龄前儿童(2至6岁)成人-儿童玩具玩耍语料库样本的TTR、NDW、VocD和MATTR分数进行了线性和非线性回归分析。这些样本与504个已知有表达性语言技能延迟儿童的样本(总共1454个样本)进行了对比。我们还进行了一项单独的子分析,研究了采样环境对词汇多样性可能产生的背景影响。

结果

只有VocD在典型发展儿童组和发展延迟儿童组之间显示出显著不同的平均分数。使用TTR实际上会误诊典型儿童,并遗漏已知有语言障碍的儿童。然而,将VocD作为玩具互动函数的计算结果具有显著性,这进一步提醒我们在将词汇多样性用作儿童表达性词汇技能的有效替代指标时要谨慎。

讨论

这项对幼儿表达性词汇特征的计算机实现算法与传统手工计算指标进行的大规模统计比较表明,只有VocD符合语言样本分析中基于证据使用的标准。然而,VocD受到样本引出背景的影响,这表明非语言因素,如与引出道具的互动,会干扰对幼儿口语词汇技能的估计。文中讨论了相关影响及建议方向。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a9df/9257278/9e10084d07ae/fpsyg-13-905789-g001.jpg

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