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Related Concept Videos

The Cochlea01:13

The Cochlea

The cochlea is a coiled structure in the inner ear that contains hair cells—the sensory receptors of the auditory system. Sound waves are transmitted to the cochlea by small bones attached to the eardrum called the ossicles, which vibrate the oval window that leads to the inner ear. This causes fluid in the chambers of the cochlea to move, vibrating the basilar membrane.
Linear Approximation in Frequency Domain01:26

Linear Approximation in Frequency Domain

Linear systems are characterized by two main properties: superposition and homogeneity. Superposition allows the response to multiple inputs to be the sum of the responses to each individual input. Homogeneity ensures that scaling an input by a scalar results in the response being scaled by the same scalar.
In contrast, nonlinear systems do not inherently possess these properties. However, for small deviations around an operating point, a nonlinear system can often be approximated as linear.

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Enhanced Cochlear Coverage and Hearing Preservation in High-Frequency Hearing Loss via Electric Acoustic Stimulation with Longer Electrode
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Real-time spectrum estimation-based dual-channel speech-enhancement algorithm for cochlear implant.

Yousheng Chen1, Qin Gong

  • 1Department of Biomedical Engineering, Tsinghua University, Beijing, 100084, PR China.

Biomedical Engineering Online
|September 26, 2012
PubMed
Summary

This study introduces a novel speech enhancement algorithm for cochlear implants (CI) that improves speech recognition in noisy conditions. The method effectively suppresses directional noise, enhancing speech clarity for CI users.

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Area of Science:

  • Biomedical Engineering
  • Signal Processing
  • Auditory Neuroscience

Background:

  • Cochlear implant (CI) performance is limited in noisy environments, necessitating improved front-end signal acquisition.
  • Directional noise significantly degrades speech recognition for CI users.

Purpose of the Study:

  • To develop and evaluate a speech enhancement algorithm for CI devices to improve speech recognition in noisy environments.
  • To suppress directional and non-stationary noise while preserving speech quality.

Main Methods:

  • A speech enhancement algorithm combining microphone array beamforming and spectral estimation was developed.
  • Directivity coefficients were estimated and updated to adapt to mobile noise conditions.
  • Maxflat filter and cepstrum method were used for parameter estimation and frame differentiation.

Main Results:

  • The algorithm demonstrated robustness against directional mobile noise and effectively enhanced desired speech.
  • Experimental results showed suppression of non-stationary noise with high signal-to-noise ratio (SNR).
  • The algorithm achieved high SNR improvement with low speech distortion in mobile testing.

Conclusions:

  • The proposed algorithm significantly enhances CI performance in noisy environments.
  • The method is robust, offering high SNR improvement and minimal speech distortion.
  • Further analysis and comparison with existing methods confirm the algorithm's efficacy.