Lexical Characteristics of the Speech Intelligibility Test: Effects on Transcription Intelligibility for Speakers With Multiple Sclerosis and Parkinson's Disease.

Purpose: Lexical characteristics of speech stimuli can significantly impact intelligibility. However, lexical characteristics of the widely used Speech Intelligibility Test (SIT) are unknown. We aimed to (a) define variation in neighborhood density, word frequency, grammatical word class, and type-t...

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Published in:Journal of Speech, Language & Hearing Research Vol. 66; pp. 3115 - 3132
Main Authors: Stipancic, Kaila L., Wilding, Gregory, Tjaden, Kris
Format: Article
Published: American Speech-Language-Hearing Association 2023 Supplement
Subjects:
Online Access:View this record in EBSCOhost
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      dt: 2023 Supplement
      vid: 66
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      pub: American Speech-Language-Hearing Association
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        10.1044/2023_JSLHR-22-00279
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        atl: Lexical Characteristics of the Speech Intelligibility Test: Effects on Transcription Intelligibility for Speakers With Multiple Sclerosis and Parkinson's Disease.
      aug:
        au:
          Stipancic, Kaila L.
          Wilding, Gregory
          Tjaden, Kris
        affil:
          Department of Communicative Disorders and Sciences, University at Buffalo, The State University of New York.
          Department of Biostatistics, University at Buffalo, The State University of New York.
      su:
        Multiple sclerosis
        Statistics
        Speech perception
        Phonological awareness
        Physiological aspects of speech
        Intelligibility of speech
        Speech evaluation
        Regression analysis
        Parkinson's disease
        Descriptive statistics
        Data analysis
        Data analysis software
        Disease complications
      sug:
        subj:
          Multiple sclerosis
          Statistics
          Speech perception
          Phonological awareness
          Physiological aspects of speech
          Intelligibility of speech
          Speech evaluation
          Regression analysis
          Parkinson's disease
          Descriptive statistics
          Data analysis
          Data analysis software
          Disease complications
      ab: Purpose: Lexical characteristics of speech stimuli can significantly impact intelligibility. However, lexical characteristics of the widely used Speech Intelligibility Test (SIT) are unknown. We aimed to (a) define variation in neighborhood density, word frequency, grammatical word class, and type-token ratio across a large corpus of SIT sentences and tests and (b) determine the relationship of lexical characteristics to speech intelligibility in speakers with multiple sclerosis (MS), Parkinson's disease (PD), and neurologically healthy controls. Method: Using an extant database of 92 speakers (32 controls, 30 speakers with MS, and 30 speakers with PD), percent correct intelligibility scores were obtained for the SIT. Neighborhood density, word frequency, word class, and type-token ratio were calculated and summed for each of the 11 sentences of each SIT test. The distribution of each characteristic across SIT sentences and tests was examined. Linear mixed-effects models were performed to assess the relationship between intelligibility and the lexical characteristics. Results: There was large variability in the distribution of lexical characteristics across this large corpus of SIT sentences and tests. Modeling revealed a relationship between intelligibility and the lexical characteristics, with word frequency and word class significantly contributing to the model. Conclusions: Three primary findings emerged: (a) There was considerable variability in lexical characteristics both within and across the large corpus of SIT tests; (b) there was not a robust association between intelligibility and the lexical characteristics; and (c) findings from a study demonstrating an effect of neighborhood density and word frequency on intelligibility were replicated. Clinical and research implications of the findings are discussed, and three exemplar SIT tests systematically controlling for neighborhood density and word frequency are provided.
      pubtype: Academic Journal
      doctype: Article
      src: R
    language: English
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