Benham Sara, Goffman Lisa, Schweickert Richard
School of Behavioral and Brain Sciences, University of Texas at Dallas.
Department of Psychological Sciences, Purdue University, West Lafayette, IN.
J Speech Lang Hear Res. 2018 Sep 19;61(9):2275-2291. doi: 10.1044/2018_JSLHR-L-18-0036.
Network science has been a valuable tool in language research for investigating relationships between complex linguistic elements but has not yet been applied to sound sequencing in production. In the present work, we used standard error-based accuracy and articulatory kinematic approaches as well as novel measures from network science to evaluate variability and sequencing errors in speech production in children with developmental language disorder (DLD; aka specific language impairment).
Twelve preschoolers with DLD and 12 age-matched controls participated in a 3-day novel word learning study. Transcription and articulatory movement data were collected to measure accuracy and variability of productions, and networks of speech productions were generated to analyze syllable co-occurrence patterns.
Results indicated that children with DLD were less accurate than children with typical language at the segmental level. Crucially, these findings did not align with performance at the articulatory level, where there were no differences in movement variability between children with DLD and those with typical language. Network analyses revealed characteristics that were not captured by standard measures of phonetic accuracy, including a larger inventory of syllable forms, more connections between the forms, and less consistent production patterns.
Network science provides significant insights into phonological learning trajectories in children with DLD and their typically developing peers. Importantly, errors in word production by children with DLD do not surface as a result of weakness in articulatory control. Instead, results suggest that speech errors in DLD may relate to deficits in sound sequencing.
网络科学在语言研究中一直是一种有价值的工具，用于研究复杂语言元素之间的关系，但尚未应用于语音产出中的音素序列。在本研究中，我们使用基于标准误差的准确性和发音运动学方法以及网络科学的新测量方法，来评估发育性语言障碍（DLD；又称特定语言障碍）儿童语音产出中的变异性和序列错误。
12名患有DLD的学龄前儿童和12名年龄匹配的对照组儿童参与了一项为期3天的新单词学习研究。收集转录和发音运动数据以测量产出的准确性和变异性，并生成语音产出网络以分析音节共现模式。
结果表明，在音段层面，患有DLD的儿童比语言正常的儿童准确性更低。至关重要的是，这些发现与发音层面的表现不一致，在发音层面，患有DLD的儿童和语言正常的儿童在运动变异性上没有差异。网络分析揭示了语音准确性标准测量未捕捉到的特征，包括更大的音节形式库、形式之间更多的连接以及更不一致的产出模式。
网络科学为患有DLD的儿童及其发育正常的同龄人在语音学习轨迹方面提供了重要见解。重要的是，患有DLD的儿童在单词产出中的错误并非由于发音控制薄弱而出现。相反，结果表明DLD中的语音错误可能与音素序列缺陷有关。
