Recurrence Quantification Analysis of Sentence-Level Speech Kinematics Purpose Current approaches to assessing sentence-level speech variability rely on measures that quantify variability across utterances and use normalization procedures that alter raw trajectory data. The current work tests the feasibility of a less restrictive nonlinear approach—recurrence quantification analysis (RQA)—via a procedural example and subsequent analysis of kinematic data. ... Research Note
Research Note  |   December 01, 2016
Recurrence Quantification Analysis of Sentence-Level Speech Kinematics
 
Author Affiliations & Notes
  • Eric S. Jackson
    University of Iowa, Iowa City
    Haskins Laboratories, New Haven, CT
  • Mark Tiede
    Haskins Laboratories, New Haven, CT
  • Michael A. Riley
    University of Cincinnati, Ohio
  • D. H. Whalen
    Haskins Laboratories, New Haven, CT
    Graduate Center, City University of New York
  • 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 Eric S. Jackson: eric-s-jackson@uiowa.edu
  • Editor: Julie Liss
    Editor: Julie Liss×
  • Associate Editor: David McFarland
    Associate Editor: David McFarland×
Article Information
Speech, Voice & Prosody / Speech / Research Notes
Research Note   |   December 01, 2016
Recurrence Quantification Analysis of Sentence-Level Speech Kinematics
Journal of Speech, Language, and Hearing Research, December 2016, Vol. 59, 1315-1326. doi:10.1044/2016_JSLHR-S-16-0008
History: Received January 7, 2016 , Revised March 31, 2016 , Accepted April 28, 2016
 
Journal of Speech, Language, and Hearing Research, December 2016, Vol. 59, 1315-1326. doi:10.1044/2016_JSLHR-S-16-0008
History: Received January 7, 2016; Revised March 31, 2016; Accepted April 28, 2016

Purpose Current approaches to assessing sentence-level speech variability rely on measures that quantify variability across utterances and use normalization procedures that alter raw trajectory data. The current work tests the feasibility of a less restrictive nonlinear approach—recurrence quantification analysis (RQA)—via a procedural example and subsequent analysis of kinematic data.

Method To test the feasibility of RQA, lip aperture (i.e., the Euclidean distance between lip-tracking sensors) was recorded for 21 typically developing adult speakers during production of a simple utterance. The utterance was produced in isolation and in carrier structures differing just in length or in length and complexity. Four RQA indices were calculated: percent recurrence (%REC), percent determinism (%DET), stability (MAXLINE), and stationarity (TREND).

Results Percent determinism (%DET) decreased only for the most linguistically complex sentence; MAXLINE decreased as a function of linguistic complexity but increased for the longer-only sentence; TREND decreased as a function of both length and linguistic complexity.

Conclusions This research note demonstrates the feasibility of using RQA as a tool to compare speech variability across speakers and groups. RQA offers promise as a technique to assess effects of potential stressors (e.g., linguistic or cognitive factors) on the speech production system.

Acknowledgments
The MATLAB procedures implemented for phase space reconstruction and RQA were obtained from the American Psychological Association Advanced Training Institute on Nonlinear Methods for Psychological Science (http://www.apa.org/science/resources/ati/nonlinear.aspx). This research was supported by National Institutes of Health Grant DC-002717 to Haskins Laboratories and National Science Foundation Grant 1513770 (awarded to Eric S. Jackson).
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