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Methodological aspects of an adaptive multidirectional pattern search to optimize speech perception using three

Bas A M Franck1, Wouter A Dreschler, Johannes Lyzenga

  • 1Academic Medical Center, Clinical and Experimental Audiology, Meibergdreef 9, 1105 AZ Amsterdam, The Netherlands. b.a.franck@amc.uva.nl

The Journal of the Acoustical Society of America
|January 22, 2005
PubMed
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This study compared adaptive and nonadaptive search procedures for optimizing speech processing. Adaptive step sizes improve reliability, but may slow convergence, highlighting a key trade-off in audio signal processing.

Area of Science:

  • Speech processing
  • Auditory perception
  • Signal processing optimization

Background:

  • Optimizing speech processing strategies like noise reduction, spectral enhancement, and spectral lift is crucial for improving listening comfort.
  • Existing nonadaptive search procedures may lack efficiency in complex auditory tasks.

Purpose of the Study:

  • To investigate the reliability and convergence of an adaptive multidirectional pattern search procedure compared to a nonadaptive one.
  • To evaluate the impact of various procedural and nonprocedural factors on optimization reliability and convergence.

Main Methods:

  • Employed a paired-comparison paradigm where subjects rated speech-in-noise fragments.
  • Utilized diverse test conditions, including different tests, initial settings, background noise types, and step size configurations.

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  • Involved seven normal-hearing subjects in the evaluation process.

    • Main Results:

    • Adaptive step sizes were found to potentially enhance the reliability of the optimization strategy.
    • Decreasing step size improved accuracy, while increasing it aided perceptual differentiation.
    • Reliability was influenced by starting point, stop criterion, step size constraints, noise, algorithms, and setting quality.

    Conclusions:

    • An adaptive step size offers benefits for speech processing optimization reliability.
    • A trade-off exists between reliability and convergence; larger step sizes enhance reliability but reduce convergence speed.
    • Careful consideration of various factors is necessary for effective optimization of speech-in-noise perception.