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Measuring Speech Recognition With a Matrix Test Using Synthetic Speech.

Theresa Nuesse1,2, Bianca Wiercinski1, Thomas Brand2,3

  • 11 Institute of Hearing Technology and Audiology, Jade University of Applied Sciences, Oldenburg, Germany.

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Summary
This summary is machine-generated.

Using synthetic speech in speech audiometry significantly reduces development time and costs. This approach offers comparable results to natural speech, enabling larger speech corpora for speech recognition tests.

Keywords:
Oldenburg sentence testspeech audiometryspeech reception thresholdsynthetic speechtext-to-speech

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Area of Science:

  • Audiology
  • Speech Science
  • Computational Linguistics

Background:

  • Speech audiometry is crucial for audiological diagnostics.
  • Developing speech recognition tests is time-consuming.
  • Current methods require extensive optimization and large speech corpora.

Purpose of the Study:

  • To investigate the feasibility of using synthetic speech to reduce development time for speech audiometry.
  • To evaluate the performance of synthetic speech in a German matrix test for speech recognition.
  • To compare speech recognition thresholds and scores between natural and synthetic speech.

Main Methods:

  • Replicated German matrix test speech material using a commercial synthetic speech system.
  • Presented both natural and synthetic speech versions of the test to 48 normal-hearing participants.
  • Evaluated performance at three different signal-to-noise ratios and fitted psychometric functions.

Main Results:

  • Speech recognition thresholds were slightly higher (0.5 dB SNR worse) for synthetic speech.
  • Slopes of psychometric functions were similar for both speech types.
  • Recognition scores were comparable to literature values and natural speech recordings.

Conclusions:

  • Synthetic speech can considerably reduce development costs and evaluation time for speech recognition tests.
  • This technology allows for expanding speech corpora with acceptable effort.
  • Synthetic speech offers a viable alternative for speech audiometry, maintaining comparable performance to natural speech.