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Extending the Hearing-Aid Speech Perception Index (HASPI): Keywords, sentences, and context.

James M Kates1

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|March 31, 2023
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Summary
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A new metric, HASPI w2, accurately predicts speech perception at the keyword level, matching the performance of the original HASPI v2 sentence-level metric. This advancement allows for detailed comparisons of word and sentence intelligibility.

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Area of Science:

  • Audiology
  • Speech Science
  • Signal Processing

Background:

  • The Hearing-Aid Speech Perception Index version 2 (HASPI v2) is an established metric for speech intelligibility.
  • HASPI v2 is derived from subject responses scored as the proportion of complete sentences correct.

Purpose of the Study:

  • To introduce HASPI w2, an extension of HASPI v2.
  • To predict the proportion of keywords correct using the same datasets as HASPI v2.
  • To enable direct comparison between word and sentence intelligibility metrics.

Main Methods:

  • Developed HASPI w2, a novel speech intelligibility metric.
  • Utilized existing datasets employed for HASPI v2 derivation.
  • Applied simulation of speech in additive noise to model context effects.

Main Results:

  • HASPI w2 demonstrates accuracy nearly identical to HASPI v2.
  • The study allows for direct comparison of proportion keywords correct and proportion sentences correct.
  • A model for context effects was developed, accounting for intelligibility loss in impaired auditory systems.

Conclusions:

  • HASPI w2 provides a reliable measure of speech intelligibility at the keyword level.
  • The developed model explains residual bias at low signal-to-noise ratios.
  • Context effects significantly influence the transformation between word and sentence intelligibility measures.