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Systematic Hearing Performance Evaluation Process for Adolescents with Cochlear Implantation at Early Ages
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A Realtime, Open-Source Speech-Processing Platform for Research in Hearing Loss Compensation.

Harinath Garudadri1, Arthur Boothroyd2, Ching-Hua Lee1

  • 1Department of Electrical and Computer Engineering, University of California, San Diego.

Conference Record. Asilomar Conference on Signals, Systems & Computers
|March 9, 2022
PubMed
Summary
This summary is machine-generated.

We created an open-source speech-processing platform for hearing aid research. This wearable system enables advanced algorithm testing and overcomes processing limitations for better hearing loss compensation.

Keywords:
Hearing aidsOpen Speech Platform (OSP)speech and audio processing

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Area of Science:

  • Audiology
  • Signal Processing
  • Wearable Technology

Background:

  • Commercial hearing aids (HAs) have basic and advanced features, but research into new algorithms is often limited by hardware and processing constraints.
  • Existing platforms may not offer the flexibility required for in-depth laboratory and field studies of advanced HA functionalities.
  • The need for a customizable, real-time, and open-source solution for hearing aid research is evident.

Purpose of the Study:

  • To present a newly developed, real-time, wearable, open-source speech-processing platform (OSP) for hearing aid research.
  • To propose enhancements and extensions for the OSP, facilitating advanced hearing aid algorithm investigation.
  • To enable researchers to configure the OSP for both lab and field studies.

Main Methods:

  • Development of a functional hearing aid using current signal processing libraries and reference designs.
  • Identification and categorization of basic and advanced features found in commercial hearing aids.
  • Implementation of a wireless protocol stack for remote parameter control and data uploading.
  • Performance evaluation of the OSP against the ANSI 3.22 standard ('Specification of Hearing Aid Characteristics').

Main Results:

  • The OSP system's performance was measured and compared with commercial hearing aids.
  • A wireless protocol stack was successfully described for remote HA control and data logging.
  • The proposed architecture allows for offloading processing from ear-level devices, mitigating CPU and inter-device communication bottlenecks.

Conclusions:

  • The developed open-source speech-processing platform offers a flexible and powerful tool for audiology and hearing aid research.
  • The OSP architecture facilitates advanced research for hearing loss compensation by overcoming current hardware limitations.
  • Future work can focus on further enhancements and extensions to the platform for broader research applications.