PREPROCESSING STRATEGIES AND SPEECH PERCEPTION IN COCHLEAR IMPLANT USERS

Abstract

Background The aim of the study was to investigate whether noise reduction algorithms are beneficial for speech perception in the presence of noise in children using cochlear implants. Further, the study also aimed to determine whether any difference in speech perception existed between different pre-processing strategies such as Adaptive Dynamic Range Optimization (ADRO), Autosensitivity Control (ASC), and the two-stage adaptive beam-forming algorithm (Beam) in different signal-tonoise ratios (SNRs). Material and Method Speech identification scores of the participants were tested in quiet with the ‘Everyday’ default setting activated. They were also tested using speech in noise at +5 dB and +10 dB SNR with ADRO, ASC, and Beam activated. Exactly 17 children using Nucleus cochlear implants for at least 1 year were tested. Results A significant difference was found between performance in quiet (in the ‘Everyday’ default setting) and in the presence of noise (with ADRO, ASC, and Beam). No significant difference was found between the 3 pre-processing strategies at both SNRs and between the 2 SNRs for all 3 strategies. Conclusions In conditions where the signal and noise emerge from in front of the listener, no influence of the pre-processing strategies was seen.