Speech understanding in background noise with the two-microphone adaptive beamformer BEAM in the Nucleus Freedom Cochlear Implant System.
OBJECTIVE
This paper evaluates the benefit of the two-microphone adaptive beamformer BEAM in the Nucleus Freedom cochlear implant (CI) system for speech understanding in background noise by CI users.


METHODS
A double-blind evaluation of the two-microphone adaptive beamformer BEAM and a hardware directional microphone was carried out with five adult Nucleus CI users. The test procedure consisted of a pre- and post-test in the lab and a 2-wk trial period at home. In the pre- and post-test, the speech reception threshold (SRT) with sentences and the percentage correct phoneme scores for CVC words were measured in quiet and background noise at different signal-to-noise ratios. Performance was assessed for two different noise configurations (with a single noise source and with three noise sources) and two different noise materials (stationary speech-weighted noise and multitalker babble). During the 2-wk trial period at home, the CI users evaluated the noise reduction performance in different listening conditions by means of the SSQ questionnaire. In addition to the perceptual evaluation, the noise reduction performance of the beamformer was measured physically as a function of the direction of the noise source.


RESULTS
Significant improvements of both the SRT in noise (average improvement of 5-16 dB) and the percentage correct phoneme scores (average improvement of 10-41%) were observed with BEAM compared to the standard hardware directional microphone. In addition, the SSQ questionnaire and subjective evaluation in controlled and real-life scenarios suggested a possible preference for the beamformer in noisy environments.


CONCLUSIONS
The evaluation demonstrates that the adaptive noise reduction algorithm BEAM in the Nucleus Freedom CI-system may significantly increase the speech perception by cochlear implantees in noisy listening conditions. This is the first monolateral (adaptive) noise reduction strategy actually implemented in a mainstream commercial CI.
Spriet
Ann
A
ExpORL, Dept. Neurosciences, KU Leuven, Leuven, Belgium. ann.spriet@esat.kuleuven.be
Van Deun
Lieselot
L
Eftaxiadis
Kyriaky
K
Laneau
Johan
J
Moonen
Marc
M
van Dijk
Bas
B
van Wieringen
Astrid
A
Wouters
Jan
J
D000328:Adult; D000465:Algorithms; D000669:Amplifiers, Electronic; D003054:Cochlear Implants / Q000592:standards*; D004867:Equipment Design; D005260:Female; D006801:Humans; D008297:Male; D008875:Middle Aged; D009622:Noise; D015203:Reproducibility of Results; D012815:Signal Processing, Computer-Assisted; D013065:Speech Intelligibility; D013067:Speech Perception; D013069:Speech Reception Threshold Test; D011795:Surveys and Questionnaires