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Speech Metrics and Samples That Differentiate Between Nonfluent/ Agrammatic and Logopenic Variants of Primary Progressive Aphasia.

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Title: Speech Metrics and Samples That Differentiate Between Nonfluent/ Agrammatic and Logopenic Variants of Primary Progressive Aphasia.
Authors: Haley, Katarina L.1 Katarina_Haley@med.unc.edu, Jacks, Adam1, Jarrett, Jordan1, Ray,a, Taylor, Cunningham, Kevin T.1, Gorno-Tempini, Maria Luisa2, Henry, Maya L.3
Source: Journal of Speech, Language & Hearing Research. Mar2021, Vol. 64 Issue 3, p754-775. 22p. 1 Diagram, 10 Charts, 1 Graph.
Subject Terms: *Stuttering, *Retrospective studies, *Aphasia, *Psychological tests, *Consonants, *Data analysis, Vowels, Inferential statistics, Statistics, Speech apraxia, Physiological aspects of speech, Confidence intervals, Mann Whitney U Test, Descriptive statistics, Intraclass correlation, Research funding, Speech, Medical coding
Abstract: Purpose: Of the three currently recognized variants of primary progressive aphasia, behavioral differentiation between the nonfluent/agrammatic (nfvPPA) and logopenic (lvPPA) variants is particularly difficult. The challenge includes uncertainty regarding diagnosis of apraxia of speech, which is subsumed within criteria for variant classification. The purpose of this study was to determine the extent to which a variety of speech articulation and prosody metrics for apraxia of speech differentiate between nfvPPA and lvPPA across diverse speech samples. Method: The study involved 25 participants with progressive aphasia (10 with nfvPPA, 10 with lvPPA, and five with the semantic variant). Speech samples included a word repetition task, a picture description task, and a story narrative task. We completed acoustic analyses of temporal prosody and quantitative perceptual analyses based on narrow phonetic transcription and then evaluated the degree of differentiation between nfvPPA and lvPPA participants (with the semantic variant serving as a reference point for minimal speech production impairment). Results: Most, but not all, articulatory and prosodic metrics differentiated statistically between the nfvPPA and lvPPA groups. Measures of distortion frequency, syllable duration, syllable scanning, and—to a limited extent—syllable stress and phonemic accuracy showed greater impairment in the nfvPPA group. Contrary to expectations, classification was most accurate in connected speech samples. A customized connected speech metric—the narrative syllable duration— yielded excellent to perfect classification accuracy. Discussion: Measures of average syllable duration in multisyllabic utterances are useful diagnostic tools for differentiating between nfvPPA and lvPPA, particularly when based on connected speech samples. As such, they are suitable candidates for automatization, large-scale study, and application to clinical practice. The observation that both speech rate and distortion frequency differentiated more effectively in connected speech than on a motor speech examination suggests that it will be important to evaluate interactions between speech and discourse production in future research. [ABSTRACT FROM AUTHOR]
Copyright of Journal of Speech, Language & Hearing Research is the property of American Speech-Language-Hearing Association and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Education Research Complete
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  Data: Speech Metrics and Samples That Differentiate Between Nonfluent/ Agrammatic and Logopenic Variants of Primary Progressive Aphasia.
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  Data: <searchLink fieldCode="AR" term="%22Haley%2C+Katarina+L%2E%22">Haley, Katarina L.</searchLink><relatesTo>1</relatesTo><i> Katarina_Haley@med.unc.edu</i><br /><searchLink fieldCode="AR" term="%22Jacks%2C+Adam%22">Jacks, Adam</searchLink><relatesTo>1</relatesTo><br /><searchLink fieldCode="AR" term="%22Jarrett%2C+Jordan%22">Jarrett, Jordan</searchLink><relatesTo>1</relatesTo><br /><searchLink fieldCode="AR" term="%22Ray%2Ca%2C+Taylor%22">Ray,a, Taylor</searchLink><br /><searchLink fieldCode="AR" term="%22Cunningham%2C+Kevin+T%2E%22">Cunningham, Kevin T.</searchLink><relatesTo>1</relatesTo><br /><searchLink fieldCode="AR" term="%22Gorno-Tempini%2C+Maria+Luisa%22">Gorno-Tempini, Maria Luisa</searchLink><relatesTo>2</relatesTo><br /><searchLink fieldCode="AR" term="%22Henry%2C+Maya+L%2E%22">Henry, Maya L.</searchLink><relatesTo>3</relatesTo>
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  Data: <searchLink fieldCode="JN" term="%22Journal+of+Speech%2C+Language+%26+Hearing+Research%22">Journal of Speech, Language & Hearing Research</searchLink>. Mar2021, Vol. 64 Issue 3, p754-775. 22p. 1 Diagram, 10 Charts, 1 Graph.
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  Data: *<searchLink fieldCode="DE" term="%22Stuttering%22">Stuttering</searchLink><br />*<searchLink fieldCode="DE" term="%22Retrospective+studies%22">Retrospective studies</searchLink><br />*<searchLink fieldCode="DE" term="%22Aphasia%22">Aphasia</searchLink><br />*<searchLink fieldCode="DE" term="%22Psychological+tests%22">Psychological tests</searchLink><br />*<searchLink fieldCode="DE" term="%22Consonants%22">Consonants</searchLink><br />*<searchLink fieldCode="DE" term="%22Data+analysis%22">Data analysis</searchLink><br /><searchLink fieldCode="DE" term="%22Vowels%22">Vowels</searchLink><br /><searchLink fieldCode="DE" term="%22Inferential+statistics%22">Inferential statistics</searchLink><br /><searchLink fieldCode="DE" term="%22Statistics%22">Statistics</searchLink><br /><searchLink fieldCode="DE" term="%22Speech+apraxia%22">Speech apraxia</searchLink><br /><searchLink fieldCode="DE" term="%22Physiological+aspects+of+speech%22">Physiological aspects of speech</searchLink><br /><searchLink fieldCode="DE" term="%22Confidence+intervals%22">Confidence intervals</searchLink><br /><searchLink fieldCode="DE" term="%22Mann+Whitney+U+Test%22">Mann Whitney U Test</searchLink><br /><searchLink fieldCode="DE" term="%22Descriptive+statistics%22">Descriptive statistics</searchLink><br /><searchLink fieldCode="DE" term="%22Intraclass+correlation%22">Intraclass correlation</searchLink><br /><searchLink fieldCode="DE" term="%22Research+funding%22">Research funding</searchLink><br /><searchLink fieldCode="DE" term="%22Speech%22">Speech</searchLink><br /><searchLink fieldCode="DE" term="%22Medical+coding%22">Medical coding</searchLink>
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: Purpose: Of the three currently recognized variants of primary progressive aphasia, behavioral differentiation between the nonfluent/agrammatic (nfvPPA) and logopenic (lvPPA) variants is particularly difficult. The challenge includes uncertainty regarding diagnosis of apraxia of speech, which is subsumed within criteria for variant classification. The purpose of this study was to determine the extent to which a variety of speech articulation and prosody metrics for apraxia of speech differentiate between nfvPPA and lvPPA across diverse speech samples. Method: The study involved 25 participants with progressive aphasia (10 with nfvPPA, 10 with lvPPA, and five with the semantic variant). Speech samples included a word repetition task, a picture description task, and a story narrative task. We completed acoustic analyses of temporal prosody and quantitative perceptual analyses based on narrow phonetic transcription and then evaluated the degree of differentiation between nfvPPA and lvPPA participants (with the semantic variant serving as a reference point for minimal speech production impairment). Results: Most, but not all, articulatory and prosodic metrics differentiated statistically between the nfvPPA and lvPPA groups. Measures of distortion frequency, syllable duration, syllable scanning, and—to a limited extent—syllable stress and phonemic accuracy showed greater impairment in the nfvPPA group. Contrary to expectations, classification was most accurate in connected speech samples. A customized connected speech metric—the narrative syllable duration— yielded excellent to perfect classification accuracy. Discussion: Measures of average syllable duration in multisyllabic utterances are useful diagnostic tools for differentiating between nfvPPA and lvPPA, particularly when based on connected speech samples. As such, they are suitable candidates for automatization, large-scale study, and application to clinical practice. The observation that both speech rate and distortion frequency differentiated more effectively in connected speech than on a motor speech examination suggests that it will be important to evaluate interactions between speech and discourse production in future research. [ABSTRACT FROM AUTHOR]
– Name: AbstractSuppliedCopyright
  Label:
  Group: Ab
  Data: <i>Copyright of Journal of Speech, Language & Hearing Research is the property of American Speech-Language-Hearing Association and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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      – Type: doi
        Value: 10.1044/2020_JSLHR-20-00445
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      – Code: eng
        Text: English
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        PageCount: 22
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    Subjects:
      – SubjectFull: Stuttering
        Type: general
      – SubjectFull: Retrospective studies
        Type: general
      – SubjectFull: Aphasia
        Type: general
      – SubjectFull: Psychological tests
        Type: general
      – SubjectFull: Consonants
        Type: general
      – SubjectFull: Data analysis
        Type: general
      – SubjectFull: Vowels
        Type: general
      – SubjectFull: Inferential statistics
        Type: general
      – SubjectFull: Statistics
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      – SubjectFull: Speech apraxia
        Type: general
      – SubjectFull: Physiological aspects of speech
        Type: general
      – SubjectFull: Confidence intervals
        Type: general
      – SubjectFull: Mann Whitney U Test
        Type: general
      – SubjectFull: Descriptive statistics
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      – SubjectFull: Intraclass correlation
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      – SubjectFull: Research funding
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      – SubjectFull: Speech
        Type: general
      – SubjectFull: Medical coding
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      – TitleFull: Speech Metrics and Samples That Differentiate Between Nonfluent/ Agrammatic and Logopenic Variants of Primary Progressive Aphasia.
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              Text: Mar2021
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              Y: 2021
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