A wavelet-based noise reduction algorithm and its clinical evaluation in cochlear implants.

Noise reduction is often essential for cochlear implant (CI) recipients to achieve acceptable speech perception in noisy environments. Most noise reduction algorithms applied to audio signals are based on time-frequency representations of the input, such as the Fourier transform. Algorithms based on other representations may also be able to provide comparable or improved speech perception and listening quality improvements.

An adaptive Australian Sentence Test in Noise (AuSTIN).

Objectives: The aim of this research is to describe the development of an adaptive Australian Sentence Test in Noise and to validate the test in terms of test-retest reliability and efficiency using data obtained from its clinical application.

Design: The relative intelligibility of 1264 Bamford-Kowal-Bench (BKB)-like sentences in the presence of competing four-talker babble was assessed with cochlear implant recipients. Intensity adjustments to the babble segments were made to reduce intersentence variability.

Cochlear implant optimized noise reduction.

Noise-reduction methods have provided significant improvements in speech perception for cochlear implant recipients, where only quality improvements have been found in hearing aid recipients. Recent psychoacoustic studies have suggested changes to noise-reduction techniques specifically for cochlear implants, due to differences between hearing aid recipient and cochlear implant recipient hearing. An optimized noise-reduction method was developed with significantly increased temporal smoothing of the signal-to-noise ratio estimate and a more aggressive gain function compared to current noise-reduction methods.

Combining directional microphone and single-channel noise reduction algorithms: a clinical evaluation in difficult listening conditions with cochlear implant users.

Objectives: This study tested a combination of algorithms designed to improve cochlear implant performance in noise. A noise reduction (NR) algorithm, based on signal to noise ratio estimation was evaluated in combination with several directional microphone algorithms available in the Cochlear CP810 sound processor.

Design: Fourteen adult unilateral cochlear implant users participated in the study.

Perceptually optimized gain function for cochlear implant signal-to-noise ratio based noise reduction.

Noise reduction in cochlear implants has achieved significant speech perception improvements through spectral subtraction and signal-to-noise ratio based noise reduction techniques. Current methods use gain functions derived through mathematical optimization or motivated by normal listening psychoacoustic experiments. Although these gain functions have been able to improve speech perception, recent studies have indicated that they are not optimal for cochlear implant noise reduction.

Clinical evaluation of signal-to-noise ratio-based noise reduction in Nucleus® cochlear implant recipients.

Objective: The aim of this study was to investigate whether a real-time noise reduction algorithm provided speech perception benefit for Cochlear™ Nucleus® cochlear implant recipients in the laboratory.

Design: The noise reduction algorithm attenuated masker-dominated channels. It estimated the signal-to-noise ratio of each channel on a short-term basis from a single microphone input, using a recursive minimum statistics method.