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Validation of an Automated Procedure for Calculating Core Lexicon From Transcripts
Sarah Grace Dalton1, Brielle C Stark2, Davida Fromm3
1Marquette University, Milwaukee, WI.
Journal of Speech, Language, and Hearing Research : JSLHR
|August 2, 2022
Summary
Automated scoring of core lexicon (CoreLex) in discourse analysis is a valid and reliable method. This approach saves time and may increase the use of discourse measures in aphasia research.
Area of Science:
- Linguistic analysis
- Computational linguistics
- Neuroscience
Background:
- Structured, monologic discourse analysis is crucial for understanding language impairments.
- Manual scoring of core lexicon (CoreLex) is time-consuming and labor-intensive.
- Automated methods are needed to improve efficiency and accessibility.
Purpose of the Study:
- To validate an automated scoring procedure for CoreLex using transcripts.
- To compare automated CoreLex scoring with manual scoring for accuracy and reliability.
- To assess the efficiency of automated CoreLex scoring.
Main Methods:
- Utilized 49 transcripts from individuals with aphasia and 48 from unimpaired individuals from AphasiaBank.
- Scored five structured monologic discourse tasks manually and via an automated CLAN command for CoreLex.
- Calculated point-to-point accuracy, reliability (intraclass correlation coefficients), and time estimates.
Main Results:
- Achieved excellent intermethod reliability with intraclass correlation coefficients ranging from .978 to .998.
- Automated scoring demonstrated significant time savings for both experienced and inexperienced CLAN users.
- Identified and examined scoring discrepancies to refine the automated process.
Conclusions:
- Automated CoreLex scoring is a valid and reliable alternative to manual scoring for monologic discourse.
- The time savings offered by automated analysis can promote broader utilization of discourse measures in aphasia research.
- Resources and instructions for the automated method are available online to facilitate adoption.
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