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Area of Science:

  • Speech Science
  • Linguistics
  • Biophysics

Background:

  • Traditional speech variability assessment methods alter raw data.
  • A less restrictive nonlinear approach is needed for analyzing speech kinematics.

Purpose of the Study:

  • To test the feasibility of Recurrence Quantification Analysis (RQA) for assessing speech variability.
  • To analyze kinematic data using RQA without normalization procedures.

Main Methods:

  • Lip aperture data were collected from 21 adult speakers producing utterances.
  • Utterances varied in isolation, length, and linguistic complexity.
  • Four RQA indices (%REC, %DET, MAXLINE, TREND) were calculated.

Main Results:

  • Percent determinism (%DET) decreased with increased linguistic complexity.
  • Stability (MAXLINE) varied with linguistic complexity and utterance length.
  • Stationarity (TREND) decreased with both increased length and complexity.

Conclusions:

  • RQA is a feasible method for comparing speech variability across speakers.
  • RQA can assess the impact of stressors like linguistic factors on speech production.