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Enhancing Electrode Location Assessment in Cochlear Implantation via Computed Tomography Image Fusion
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Sparse Nonnegative Matrix Factorization Strategy for Cochlear Implants.

Hongmei Hu1, Mark E Lutman2, Stephan D Ewert3

  • 1Institute of Sound and Vibration Research, University of Southampton, UK Medizinische Physik, Universität Oldenburg and Cluster of Excellence "Hearing4all", Oldenburg, Germany hongmei.hu@uni-oldenburg.de.

Trends in Hearing
|January 2, 2016
PubMed
Summary
This summary is machine-generated.

This study introduces a novel cochlear implant (CI) algorithm using nonnegative matrix factorization (NMF) to enhance speech processing in noise. While showing promise for normal-hearing individuals, it yielded limited improvements for CI users.

Keywords:
babble noisecochlear implantnonnegative matrix factorizationspeech enhancementspeech recognitionvocoder

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Area of Science:

  • Auditory Neuroscience
  • Signal Processing
  • Biomedical Engineering

Background:

  • Current cochlear implant (CI) strategies transmit speech information via waveform envelopes.
  • Speech processing in CIs is crucial for effective brain information transfer, particularly in noisy environments where envelopes are less robust.
  • Sparse transformations like nonnegative matrix factorization (NMF) can potentially enhance frequency-decomposed speech envelopes.

Purpose of the Study:

  • To develop and evaluate a novel CI processing algorithm utilizing NMF on the envelopogram for improved performance in noisy conditions.
  • To optimize the sparsity constraint parameter of the NMF algorithm using objective and subjective measures.
  • To assess the algorithm's effectiveness for speech intelligibility and perception in normal-hearing and CI users.

Main Methods:

  • A new CI algorithm was developed by applying NMF to the envelopogram across 22 frequency channels.
  • The critical sparsity constraint parameter was tuned using objective measures.
  • Performance was evaluated using speech in eight-talker babble noise through vocoder simulations with normal-hearing subjects and direct experiments with CI users.

Main Results:

  • Vocoder simulations with normal-hearing subjects demonstrated significant speech intelligibility enhancement with the NMF algorithm.
  • CI subjects showed no significant overall improvement compared to the standard advanced combination encoder (ACE) algorithm.
  • A trend towards a 10 percentage point improvement in word identification at +15 dB SNR was observed in CI users, with reduced performance spread.

Conclusions:

  • The NMF-based CI coding strategy shows potential for enhancing speech perception, particularly in reducing performance variability for cochlear implant users.
  • Further research and optimization may be needed to translate observed benefits to significant improvements in CI patient outcomes.
  • The algorithm's effectiveness in improving speech intelligibility for normal-hearing individuals suggests its potential utility in auditory signal processing research.