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Validation of an Automated Procedure for Calculating Core Lexicon From Transcripts

Authors :
Sarah Grace Dalton
Brielle C. Stark
Davida Fromm
Kristen Apple
Brian MacWhinney
Amanda Rensch
Madyson Rowedder
Source :
Journal of Speech, Language, and Hearing Research. 65:2996-3003
Publication Year :
2022
Publisher :
American Speech Language Hearing Association, 2022.

Abstract

Purpose: The aim of this study was to advance the use of structured, monologic discourse analysis by validating an automated scoring procedure for core lexicon (CoreLex) using transcripts. Method: Forty-nine transcripts from persons with aphasia and 48 transcripts from persons with no brain injury were retrieved from the AphasiaBank database. Five structured monologic discourse tasks were scored manually by trained scorers and via automation using a newly developed CLAN command based upon previously published lists for CoreLex. Point-to-point (or word-by-word) accuracy and reliability of the two methods were calculated. Scoring discrepancies were examined to identify errors. Time estimates for each method were calculated to determine if automated scoring improved efficiency. Results: Intraclass correlation coefficients for the tasks ranged from .998 to .978, indicating excellent intermethod reliability. Automated scoring using CLAN represented a significant time savings for an experienced CLAN user and for inexperienced CLAN users following step-by-step instructions. Conclusions: Automated scoring of CoreLex is a valid and reliable alternative to the current gold standard of manually scoring CoreLex from transcribed monologic discourse samples. The downstream time saving of this automated analysis may allow for more efficient and broader utilization of this discourse measure in aphasia research. To further encourage the use of this method, go to https://aphasia.talkbank.org/discourse/CoreLexicon/ for materials and the step-by-step instructions utilized in this project. Supplemental Material: https://doi.org/10.23641/asha.20399304

Details

ISSN :
15589102 and 10924388
Volume :
65
Database :
OpenAIRE
Journal :
Journal of Speech, Language, and Hearing Research
Accession number :
edsair.doi.dedup.....8229446c8cd1808dd9a816ab900009fc
Full Text :
https://doi.org/10.1044/2022_jslhr-21-00473