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Validation of an Automated Procedure for Calculating Core Lexicon From Transcripts
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 w...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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American Speech-Language-Hearing Association
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9911121/ https://www.ncbi.nlm.nih.gov/pubmed/35917459 http://dx.doi.org/10.1044/2022_JSLHR-21-00473 |
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author | Dalton, Sarah Grace Stark, Brielle C. Fromm, Davida Apple, Kristen MacWhinney, Brian Rensch, Amanda Rowedder, Madyson |
author_facet | Dalton, Sarah Grace Stark, Brielle C. Fromm, Davida Apple, Kristen MacWhinney, Brian Rensch, Amanda Rowedder, Madyson |
author_sort | Dalton, Sarah Grace |
collection | PubMed |
description | 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 |
format | Online Article Text |
id | pubmed-9911121 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | American Speech-Language-Hearing Association |
record_format | MEDLINE/PubMed |
spelling | pubmed-99111212023-02-10 Validation of an Automated Procedure for Calculating Core Lexicon From Transcripts Dalton, Sarah Grace Stark, Brielle C. Fromm, Davida Apple, Kristen MacWhinney, Brian Rensch, Amanda Rowedder, Madyson J Speech Lang Hear Res Language 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 American Speech-Language-Hearing Association 2022-08 2022-08-02 /pmc/articles/PMC9911121/ /pubmed/35917459 http://dx.doi.org/10.1044/2022_JSLHR-21-00473 Text en Copyright © The Authors https://creativecommons.org/licenses/by/4.0/ This work is licensed under a Creative Commons Attribution 4.0 International License (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Language Dalton, Sarah Grace Stark, Brielle C. Fromm, Davida Apple, Kristen MacWhinney, Brian Rensch, Amanda Rowedder, Madyson Validation of an Automated Procedure for Calculating Core Lexicon From Transcripts |
title | Validation of an Automated Procedure for Calculating Core Lexicon From Transcripts |
title_full | Validation of an Automated Procedure for Calculating Core Lexicon From Transcripts |
title_fullStr | Validation of an Automated Procedure for Calculating Core Lexicon From Transcripts |
title_full_unstemmed | Validation of an Automated Procedure for Calculating Core Lexicon From Transcripts |
title_short | Validation of an Automated Procedure for Calculating Core Lexicon From Transcripts |
title_sort | validation of an automated procedure for calculating core lexicon from transcripts |
topic | Language |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9911121/ https://www.ncbi.nlm.nih.gov/pubmed/35917459 http://dx.doi.org/10.1044/2022_JSLHR-21-00473 |
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