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Automating Error Frequency Analysis via the Phonemic Edit Distance Ratio.

Michael Smith1, Kevin T Cunningham1, Katarina L Haley1

  • 1Division of Speech and Hearing Sciences, Department of Allied Health Sciences, University of North Carolina, Chapel Hill.

Journal of Speech, Language, and Hearing Research : JSLHR
|June 7, 2019
PubMed
Summary

This study validates an automated method using the Levenshtein edit distance to accurately measure phonemic error frequency in speech after stroke. This efficient tool aids research and clinical practice by replacing time-consuming manual analysis.

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Area of Science:

  • Neurology
  • Speech-Language Pathology
  • Computational Linguistics

Background:

  • Communication disorders frequently cause speech sound errors perceived as phonemic errors.
  • Manual calculation of phonemic error frequency is time-intensive, limiting its use in research and clinical settings.

Purpose of the Study:

  • To validate an automated analysis using the unweighted Levenshtein edit distance for quantifying phonemic error frequency post-left hemisphere stroke.
  • To provide an efficient alternative to manual methods for assessing speech sound errors.

Main Methods:

  • Phonetic transcription of audio-recorded speech samples from 65 post-stroke speakers repeating single words.
  • Calculation of the phonemic edit distance ratio by comparing transcribed productions to target words.
  • Validation against manually calculated phonemic error frequency.

Main Results:

  • Excellent convergent validity was found between the automated phonemic edit distance ratio and manual error frequency calculations.
  • The automated method demonstrated nearly perfect correlations and negligible mean differences.
  • Results were consistently replicated across different speech samples and computation applications.

Conclusions:

  • The phonemic edit distance ratio is a valid, simple, and efficient method for estimating phonemic error rates.
  • This automated approach is suitable for immediate application in speech research and clinical practice.
  • It offers a reliable substitute for manual error frequency calculations without requiring additional complex steps.