Predicting Intelligibility Gains in Dysarthria Through Automated Speech Feature Analysis Purpose Behavioral speech modifications have variable effects on the intelligibility of speakers with dysarthria. In the companion article, a significant relationship was found between measures of speakers' baseline speech and their intelligibility gains following cues to speak louder and reduce rate (Fletcher, McAuliffe, Lansford, Sinex, & Liss, 2017). This study ... Research Article
Research Article  |   November 09, 2017
Predicting Intelligibility Gains in Dysarthria Through Automated Speech Feature Analysis
 
Author Affiliations & Notes
  • Annalise R. Fletcher
    Department of Communication Disorders, University of Canterbury, Christchurch, New Zealand
  • Alan A. Wisler
    School of Electrical, Computer and Energy Engineering, Arizona State University, Tempe
  • Megan J. McAuliffe
    Department of Communication Disorders, University of Canterbury, Christchurch, New Zealand
  • Kaitlin L. Lansford
    School of Communication Science & Disorders, Florida State University, Tallahassee
  • Julie M. Liss
    Department of Speech and Hearing Science, Arizona State University, Tempe
  • Disclosure: The authors have declared that no competing interests existed at the time of publication.
    Disclosure: The authors have declared that no competing interests existed at the time of publication.×
  • Correspondence to Annalise Fletcher: annalise.fletcher@canterbury.ac.nz
  • Editor-in-Chief: Krista Wilkinson
    Editor-in-Chief: Krista Wilkinson×
  • Editor: Jeannette Hoit
    Editor: Jeannette Hoit×
Article Information
Speech, Voice & Prosodic Disorders / Dysarthria / Hearing & Speech Perception / Acoustics / Speech / Research Articles
Research Article   |   November 09, 2017
Predicting Intelligibility Gains in Dysarthria Through Automated Speech Feature Analysis
Journal of Speech, Language, and Hearing Research, November 2017, Vol. 60, 3058-3068. doi:10.1044/2017_JSLHR-S-16-0453
History: Received December 15, 2016 , Revised June 27, 2017 , Accepted June 27, 2017
 
Journal of Speech, Language, and Hearing Research, November 2017, Vol. 60, 3058-3068. doi:10.1044/2017_JSLHR-S-16-0453
History: Received December 15, 2016; Revised June 27, 2017; Accepted June 27, 2017

Purpose Behavioral speech modifications have variable effects on the intelligibility of speakers with dysarthria. In the companion article, a significant relationship was found between measures of speakers' baseline speech and their intelligibility gains following cues to speak louder and reduce rate (Fletcher, McAuliffe, Lansford, Sinex, & Liss, 2017). This study reexamines these features and assesses whether automated acoustic assessments can also be used to predict intelligibility gains.

Method Fifty speakers (7 older individuals and 43 with dysarthria) read a passage in habitual, loud, and slow speaking modes. Automated measurements of long-term average spectra, envelope modulation spectra, and Mel-frequency cepstral coefficients were extracted from short segments of participants' baseline speech. Intelligibility gains were statistically modeled, and the predictive power of the baseline speech measures was assessed using cross-validation.

Results Statistical models could predict the intelligibility gains of speakers they had not been trained on. The automated acoustic features were better able to predict speakers' improvement in the loud condition than the manual measures reported in the companion article.

Conclusions These acoustic analyses present a promising tool for rapidly assessing treatment options. Automated measures of baseline speech patterns may enable more selective inclusion criteria and stronger group outcomes within treatment studies.

Acknowledgments
This work was supported by a Fulbright New Zealand Graduate Award, granted to Annalise R. Fletcher.
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