Hansson Kristina, Bååth Rasmus, Löhndorf Simone, Sahlén Birgitta, Sikström Sverker
Department of Clinical Sciences, Lund, Logopedics, Phoniatrics and Audiology, Lund University, Lund, Sweden.
Lund University Cognitive Science, Lund University, Lund, Sweden.
J Psycholinguist Res. 2016 Oct;45(5):1183-99. doi: 10.1007/s10936-015-9398-7.
We propose a method to quantify semantic linguistic maturity (SELMA) based on a high dimensional semantic representation of words created from the co-occurrence of words in a large text corpus. The method was applied to oral narratives from 108 children aged 4;0-12;10. By comparing the SELMA measure with maturity ratings made by human raters we found that SELMA predicted the rating of semantic maturity made by human raters over and above the prediction made using a child's age and number of words produced. We conclude that the semantic content of narratives changes in a predictable pattern with children's age and argue that SELMA is a measure quantifying semantic linguistic maturity. The study opens up the possibility of using quantitative measures for studying the development of semantic representation in children's narratives, and emphasizes the importance of word co-occurrences for understanding the development of meaning.
我们提出了一种基于大文本语料库中词共现所创建的词的高维语义表示来量化语义语言成熟度（SELMA）的方法。该方法应用于108名年龄在4岁0个月至12岁10个月的儿童的口头叙述。通过将SELMA测量结果与人类评分者给出的成熟度评级进行比较，我们发现，除了使用儿童年龄和所产生的单词数量进行预测之外，SELMA还能预测人类评分者给出的语义成熟度评级。我们得出结论，叙述的语义内容会随着儿童年龄的增长而以可预测的模式变化，并认为SELMA是一种量化语义语言成熟度的指标。该研究开启了使用定量测量方法来研究儿童叙述中语义表示发展的可能性，并强调了词共现对于理解意义发展的重要性。
