Bristol Speech and Language Therapy Research Unit, North Bristol NHS Trust, Bristol, UK.
Bristol Dental School, University of Bristol, Bristol, UK.
Clin Linguist Phon. 2021 Aug 3;35(8):761-778. doi: 10.1080/02699206.2020.1827458. Epub 2020 Oct 6.
Connected speech (CS) is an important component of child speech assessment in both clinical practice and research. There is debate in the literature regarding what size sample of CS is required to facilitate reliable measures of speech output. The aim of this study was to identify the minimum number of word tokens required to obtain a reliable measure of CS across a range of measures. Participants were 776 5-year-olds from a longitudinal community population cohort study (Avon Longitudinal Study of Parents and Children, ALSPAC). Children's narratives from a story retell task were audio-recorded and phonetically transcribed. Automatic analysis of the transcribed speech samples was completed using an automated transcription and analysis system. Measures of speech performance extracted included: a range of profiles of percentage consonant correct; frequency of substitutions, omissions, distortions and additions (SODA); percentage of syllable and stress pattern matches; and a measure of whole word complexity (Phonological Mean Length of Utterance, pMLU). Statistical analyses compared these measures at different CS sample sizes in increments using averages and weighted moving averages, and investigated how measures performed between CS samples grouped into word tokens of at least 50, 75 and 100, and restricted to samples of 50-74, 75-99 and 100-125. Key findings showed that sample sizes of 75 word tokens and above showed minimal differences in most measures of speech output, suggesting that the minimum requirement for samples of CS is a word count of 75. The exception to this is in the case of pMLU and measures of substitutions and distortions when a word count of 100 is recommended.
连读语音 (CS) 是临床实践和研究中儿童言语评估的一个重要组成部分。在文献中,对于 CS 需要多大的样本量才能促进可靠的言语产出测量存在争议。本研究的目的是确定在一系列测量中获得可靠 CS 测量所需的最小单词标记数。参与者是来自纵向社区人群队列研究(阿冯纵向研究父母和孩子,ALSPAC)的 776 名 5 岁儿童。从故事复述任务中录制并语音转录了儿童的叙述。使用自动转录和分析系统对转录的语音样本进行自动分析。提取的语音表现测量包括:一系列百分比辅音正确的比例;替代、省略、扭曲和添加的频率 (SODA);音节和重音模式匹配的百分比;以及整体单词复杂度的测量(语音平均长度单位,pMLU)。统计分析使用平均值和加权移动平均值比较了不同 CS 样本大小的这些测量值,并研究了如何在 CS 样本分组为至少 50、75 和 100 个单词标记之间以及限制为 50-74、75-99 和 100-125 个单词标记之间的测量值表现。主要发现表明,75 个单词标记以上的样本大小在大多数言语产出测量中差异最小,表明 CS 样本的最小要求是单词数为 75。这一规则的例外情况是在 pMLU 和替代和扭曲测量中,建议使用 100 个单词计数。