Automated grammatical tagging of child language samples.
Automated grammatical tagging of child language samples.
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儿童语言样本的自动语法标记。
DOI：
10.1044/jslhr.4203.727
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发表时间：
1999
期刊：
影响因子：
--
通讯作者：
Johnson,BW
中科院分区：
文献类型：
--
作者：
Channell,RW;Johnson,BW
最近使用概率方法对单词进行自动语法分类（“标记”）的研究报告了相当高的准确性——与对各种文本中的单词进行手动标记的一致性超过 95%。然而，测试这种方法的文本是由成年人撰写并由出版商编辑的。本研究检验了此类方法对 30 名正常发育儿童的转录对话语言样本进行标记的准确性。按逐字计算，自动准确率范围为 92.9% 至 97.4%，平均为 95.1%。正确标记整个话语的准确度较低，范围为 60.5% 到 90.3%，平均为 77.7%。语言样本编码的概率方法具有作为儿童语言研究的可行工具的潜力。在广泛使用该技术之前，有必要进一步研究和改进自动语法标记。
Recent studies of the automated grammatical categorization ("tagging") of words using probabilistic methods have reported substantial levels of accuracy—over 95% agreement with manual tagging for words from a variety of texts. However, the texts with which this method has been tested were written by adults and edited by publishers. The present study examined the accuracy with which such methods could tag transcribed conversational language samples from 30 normally developing children. On a word-by-word basis, automated accuracy levels ranged from 92.9% to 97.4%, averaging 95.1%. Accuracy at correctly tagging whole utterances was lower, ranging from 60.5% to 90.3%, with an average of 77.7%. Probabilistic methods of coding language samples hold potential as a viable tool for child language research. Further study and improvement of automated grammatical tagging is warranted and necessary before widespread use can be made of this technology.