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ParAlg: A Paraphasia Algorithm for Multinomial Classification of Picture Naming Errors.

Marianne Casilio1, Gerasimos Fergadiotis2, Alexandra C Salem3

  • 1Vanderbilt University Medical Center, Nashville, TN.

Journal of Speech, Language, and Hearing Research : JSLHR
|February 15, 2023
PubMed
Summary
This summary is machine-generated.

The updated Paraphrasia Classification Algorithm (ParAlg) accurately codes picture naming errors, with the orthographic-lexical method showing superior performance. This algorithm offers an efficient alternative to manual scoring for anomia assessment.

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Area of Science:

  • Linguistics
  • Computational Linguistics
  • Speech-Language Pathology

Background:

  • Paraphasias are common errors in picture naming, often assessed manually.
  • A preliminary Paraphrasia Classification Algorithm (ParAlg) showed promise for automating this process.

Purpose of the Study:

  • To present an updated Paraphrasia Classification Algorithm (ParAlg) utilizing multinomial classification.
  • To comprehensively evaluate the performance of the updated ParAlg using two distinct transcription methods.

Main Methods:

  • Classified 11,999 responses from the Philadelphia Naming Test using ParAlg.
  • Compared ParAlg performance between phonemic-only and orthographic-lexical transcription configurations.
  • Evaluated agreement using positive predictive value, sensitivity, specificity, and F1 score against human annotations.

Main Results:

  • High agreement was observed between ParAlg-generated and human-annotated paraphasia codes.
  • The orthographic-lexical configuration (F1=.87) significantly outperformed the phonemic-only configuration (F1=.78).
  • Qualitative analysis revealed misclassifications due to phonological and semantic similarity judgments.

Conclusions:

  • The updated Paraphrasia Classification Algorithm (ParAlg) is an accurate and efficient tool for paraphasia scoring.
  • Orthographic transcription of lexical responses enhances ParAlg's performance.
  • ParAlg shows potential as a software application for anomia assessment.