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Related Experiment Videos

Nucleus 24 advanced encoder conversion study: performance versus preference.

Margaret W Skinner1, Patti L Arndt, Steven J Staller

  • 1Department of Otolaryngology-Head and Neck Surgery, Washington University School of Medicine, St Louis, Missouri 63110, USA.

Ear and Hearing
|March 9, 2002
PubMed
Summary
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Adult cochlear implant users preferred speech coding strategies like Advanced Combination Encoder (ACE) that improved their hearing performance, especially in noisy environments. Individual differences in strategy preference and usage were observed, with most users favoring a single strategy.

Area of Science:

  • Audiology
  • Biomedical Engineering
  • Neuroscience

Background:

  • Cochlear implants are crucial for restoring hearing in deaf individuals.
  • Speech coding strategies significantly impact speech recognition performance.
  • Comparing Advanced Combination Encoder (ACE), Continuous Interleaved Sampling (CIS), and Spectral Peak (SPEAK) is essential for optimizing cochlear implant efficacy.

Purpose of the Study:

  • To evaluate the safety and effectiveness of ACE and CIS speech coding strategies against SPEAK in Nucleus 24 implant users.
  • To test if preferred strategies yield higher speech recognition scores compared to non-preferred ones.

Main Methods:

  • 100 postlinguistically deaf adults with Nucleus 24 implants participated.
  • Subjects used ACE and CIS strategies for 6-week periods, with SPEAK as baseline.

Related Experiment Videos

  • Speech recognition was assessed using various tests (consonants, vowels, words, sentences) in quiet and noise.

    • Main Results:

    • 56 out of 62 subjects preferred a single strategy (ACE: 59.7%, SPEAK: 22.6%, CIS: 8.0%).
    • Preferred strategies generally led to better performance on sentence tests, particularly in noise.
    • Strong agreement existed between strategy preference, usage duration, and perceived benefit across listening situations.

    Conclusions:

    • A significant link exists between user-preferred strategies and improved speech recognition, especially in noise.
    • Individual variability in strategy preference and performance necessitates personalized fitting approaches.
    • Most users prefer a single strategy, but some benefit from using multiple strategies for diverse listening environments.