Automated grammatical tagging of child language samples.
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 b...
| Publicado en: | Journal of Speech, Language & Hearing Research Vol. 42; no. 3; pp. 727 - 735 |
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| Autores principales: | , |
| Formato: | research tables/charts Journal Article |
| Publicado: |
American Speech-Language-Hearing Association
Jun1999
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=107228611&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 107228611 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 10924388 1SM jtl: Journal of Speech, Language & Hearing Research issn: 10924388 maglogo: N pubinfo: dt: Jun1999 vid: 42 iid: 3 pid: 42 pub: American Speech-Language-Hearing Association place: Rockville, Maryland artinfo: ui: 107228611 107228611 1999081899 10.1044/jslhr.4203.727 NLM10391635 107228611 ppf: 727 ppct: 8 formats: fmt: – @attributes: type: T – @attributes: type: P tig: atl: Automated grammatical tagging of child language samples. aug: au: Channell RW Johnson BW affil: Brigham Young University, Provo, UT sug: subj: Grammar Evaluation Speech Sample In Infancy and Childhood Speech and Language Assessment Methods Funding Source Conversation Probability Comparative Studies Automation Child, Preschool Child Software Reliability Descriptive Statistics Data Collection Methods Human Child, Preschool: 2-5 years Child: 6-12 years ab: 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. pubtype: Academic Journal doctype: research tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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