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Subglottal Impedance-Based Inverse Filtering of Voiced Sounds Using Neck Surface Acceleration.

Matías Zañartu1, Julio C Ho2, Daryush D Mehta3

  • 1Department of Electronic Engineering, Universidad Técnica Federico Santa Maíia, Valparaíso, Chile.

IEEE Transactions on Audio, Speech, and Language Processing
|November 18, 2014
PubMed
Summary
This summary is machine-generated.

A new non-invasive method, subglottal impedance-based inverse filtering (IBIF), accurately estimates glottal airflow using neck acceleration. This advancement aids in assessing voice disorders and improving speech communication technologies.

Keywords:
Inverse filteringaccelerometerambulatory monitoringglottal airflowglottal sourceneck vibrationvocal foldsvoice production

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Area of Science:

  • Bioacoustics
  • Speech Science
  • Medical Engineering

Background:

  • Accurate estimation of glottal airflow is crucial for understanding voice production and diagnosing voice disorders.
  • Traditional methods often rely on invasive techniques or focus on the supraglottal vocal tract, limiting their clinical applicability.
  • Ambulatory assessment of vocal function has been restricted to basic parameters like phonation duration, loudness, and pitch.

Purpose of the Study:

  • To propose and validate a novel model-based inverse filtering scheme for non-invasive estimation of aerodynamic sound sources at the glottis.
  • To introduce subglottal impedance-based inverse filtering (IBIF) using neck acceleration signals.
  • To assess the accuracy and potential clinical applications of the IBIF method for voice disorder assessment.

Main Methods:

  • Developed a model-based inverse filtering scheme (IBIF) utilizing mechano-acoustic impedance representations.
  • Employed a physiologically-based transmission line model and a lumped skin surface representation.
  • Incorporated a subject-specific calibration protocol to account for individual physiological variations.
  • Used lightweight accelerometers placed on the extrathoracic trachea to capture neck acceleration signals.

Main Results:

  • The subglottal IBIF scheme provides accurate estimates of glottal airflow and its time derivative.
  • Preliminary results show comparable accuracy to existing aerodynamics-based clinical methods for sustained vowels.
  • Achieved a mean absolute error of less than 10% for key glottal airflow measures (maximum flow declination rate, amplitude of modulation component).
  • Demonstrated potential for advancing ambulatory vocal function assessment beyond basic parameters.

Conclusions:

  • Subglottal IBIF offers a promising non-invasive approach for accurate glottal airflow estimation.
  • The method has significant implications for the clinical assessment of voice disorders, particularly those related to vocal hyperfunction.
  • IBIF enhances ambulatory vocal function monitoring and holds potential for broader applications in speech communication.