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April 3, 2026JASA Express LettersOpen Access

Objective comparison of audiometric profile frameworks across large-scale datasets

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CXChen Xu

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Overview

Comparison of audiometric profiles reveals performance similarities across large datasets, indicating robustness of frameworks.

Key Points

  • The study aims to investigate how different datasets affect the performance of audiometric profiling frameworks.
  • Compared six audiometric profiling frameworks
  • Analyzed five large-scale datasets from the U.S. and Germany
  • Used Davies-Bouldin score for clustering performance evaluation
  • Applied principal component analysis for framework comparison
  • Clustering performance was comparable across datasets
  • Profile-specific performance differences were noted
  • Findings highlight the robustness of audiogram-based classifications across large samples

Cite This Study

Chen Xu (2026) studied this question.

synapsesocial.com/papers/69cf5fe05a333a821460eafbhttps://doi.org/10.1121/10.0043212
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