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A Hearing Test Simulator GUI for clinical testing of speech recognition.

Serkan Tokgoz1, Stephanie Tittle2, Linda Thibodeau2

  • 1Department of Electrical Engineering, The University of Texas at Dallas, Richardson, TX, 75080.

Proceedings of Meetings on Acoustics. Acoustical Society of America
|June 21, 2021
PubMed
Summary

This study introduces a MATLAB GUI for speech recognition testing in noisy conditions. It reliably measures word recognition rates across various noise types and signal-to-noise ratios for clinical and engineering applications.

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Area of Science:

  • Audiology
  • Signal Processing
  • Human-Computer Interaction

Background:

  • Assessing speech recognition in noise is crucial for understanding auditory perception.
  • Existing methods for testing in simulated noisy environments can be costly and complex.
  • A need exists for accessible tools for evaluating speech recognition performance under varying signal-to-noise ratios (SNR).

Purpose of the Study:

  • To present a MATLAB-based Graphical User Interface (GUI) for speech recognition testing.
  • To evaluate subjects' speech perception abilities in diverse noisy environments.
  • To provide a cost-effective and reliable simulation for clinical and engineering evaluations.

Main Methods:

  • Development of a MATLAB-based GUI for presenting auditory stimuli.
  • Recording and analyzing subjects' word perception responses.
  • Collecting test data under controlled conditions with varying noise types (babble, traffic, machinery, white noise) and SNRs.
  • Saving word recognition rates and scores into a database for analysis.

Main Results:

  • The GUI enables accurate identification of correctly perceived words.
  • Word recognition rates can be systematically recorded across different noise conditions and SNRs.
  • Test data and scores are stored, facilitating repeated testing cycles and subsequent analysis.
  • The system provides a reliable and cost-effective method for simulating real-world auditory challenges.

Conclusions:

  • The developed MATLAB GUI offers a valuable tool for speech recognition testing in noisy environments.
  • It supports both clinical evaluation of auditory function and engineering research in signal processing.
  • The software provides a reliable, cost-effective, and flexible platform for assessing speech perception under controlled adverse conditions.