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Optimized loudness-function estimation for categorical loudness scaling data.

Dirk Oetting1, Thomas Brand2, Stephan D Ewert2

  • 1Project Group Hearing, Speech and Audio Technology of the Fraunhofer IDMT and Cluster of Excellence Hearing4all, Marie-Curie-Str. 2, 26129 Oldenburg, Germany; Medizinische Physik and Cluster of Excellence Hearing4all, Universität Oldenburg, 26111 Oldenburg, Germany.

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Summary
This summary is machine-generated.

This study improved loudness function estimation from categorical loudness scaling (CLS) data. The new method enhances test-retest reliability, especially for hearing-impaired listeners in clinical settings.

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Area of Science:

  • Audiology
  • Psychoacoustics
  • Hearing Science

Background:

  • Categorical loudness scaling (CLS) is a clinical tool for assessing individual loudness perception without listener training.
  • Accurate loudness function estimation is crucial for audiological assessments and hearing aid fitting.
  • Existing methods for loudness function estimation from CLS data may have limitations in test-retest reliability.

Purpose of the Study:

  • To investigate and compare different methods for loudness function estimation from CLS data.
  • To evaluate the test-retest behavior of various loudness function estimation techniques.
  • To propose an improved method for adaptive CLS, enhancing accuracy and reliability.

Main Methods:

  • Conducted four CLS runs with 13 normal-hearing and 11 hearing-impaired listeners.
  • Compared loudness function fitting approaches by minimizing errors in level and loudness domains.
  • Modified hearing threshold level (HTL) extraction and investigated uncomfortable loudness level (UCL) estimation.

Main Results:

  • The modified HTL estimation showed better agreement with pure-tone audiometric thresholds.
  • Computer simulations indicated reduced estimation error for UCL with sparse upper-range loudness data.
  • The suggested modifications improved overall test-retest behavior of CLS data analysis.

Conclusions:

  • The proposed fitting method offers improved test-retest behavior for CLS data.
  • This method is particularly advantageous for clinical data with high variability or absent upper-range responses.
  • Enhanced loudness function estimation can lead to more accurate audiological assessments.