Modelling speech reception thresholds and their improvements due to spatial noise reduction algorithms in bimodal cochlear implant users.

Spatial noise reduction algorithms ("beamformers") can considerably improve speech reception thresholds (SRTs) for bimodal cochlear implant (CI) users. The goal of this study was to model SRTs and SRT-benefit due to beamformers for bimodal CI users. Two existing model approaches varying in computational complexity and binaural processing assumption were compared: (i) the framework of auditory discrimination experiments (FADE) and (ii) the binaural speech intelligibility model (BSIM), both with CI and aided hearing-impaired front-ends. The exact same acoustic scenarios, and open-access beamformers as in the comparison clinical study Zedan et al. (2021) were used to quantify goodness of prediction. FADE was capable of modeling SRTs ab-initio, i.e., no calibration of the model was necessary to achieve high correlations and low root-mean square errors (RMSE) to both, measured SRTs (r = 0.85, RMSE = 2.8 dB) and to measured SRT-benefits (r = 0.96). BSIM achieved somewhat poorer predictions to both, measured SRTs (r = 0.78, RMSE = 6.7 dB) and to measured SRT-benefits (r = 0.91) and needs to be calibrated for matching average SRTs in one condition. Greatest deviations in predictions of BSIM were observed in diffuse multi-talker babble noise, which were not found with FADE. SRT-benefit predictions of both models were similar to instrumental signal-to-noise ratio (iSNR) improvements due to the beamformers. This indicates that FADE is preferrable for modeling absolute SRTs. However, for prediction of SRT-benefit due to spatial noise reduction algorithms in bimodal CI users, the average iSNR is a much simpler approach with similar performance.

Speech Intelligibility and Spatial Release From Masking Improvements Using Spatial Noise Reduction Algorithms in Bimodal Cochlear Implant Users.

This study investigated the speech intelligibility benefit of using two different spatial noise reduction algorithms in cochlear implant (CI) users who use a hearing aid (HA) on the contralateral side (bimodal CI users). The study controlled for head movements by using head-related impulse responses to simulate a realistic cafeteria scenario and controlled for HA and CI manufacturer differences by using the master hearing aid platform (MHA) to apply both hearing loss compensation and the noise reduction algorithms (beamformers). Ten bimodal CI users with moderate to severe hearing loss contralateral to their CI participated in the study, and data from nine listeners were included in the data analysis. The beamformers evaluated were the adaptive differential microphones (ADM) implemented independently on each side of the listener and the (binaurally implemented) minimum variance distortionless response (MVDR). For frontal speech and stationary noise from either left or right, an improvement (reduction) of the speech reception threshold of 5.4 dB and 5.5 dB was observed using the ADM, and 6.4 dB and 7.0 dB using the MVDR, respectively. As expected, no improvement was observed for either algorithm for colocated speech and noise. In a 20-talker babble noise scenario, the benefit observed was 3.5 dB for ADM and 7.5 dB for MVDR. The binaural MVDR algorithm outperformed the bilaterally applied monaural ADM. These results encourage the use of beamformer algorithms such as the ADM and MVDR by bimodal CI users in everyday life scenarios.