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

Abstract

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.

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

“…Bimodal CI users experience a considerable benefit when using spatial noise reduction algorithms (‘beamformers’) as has been shown in multiple studies that tested their speech-in-noise performance in simplified and realistic acoustic scenarios ( Buechner, Dyballa, Hehrmann, Fredelake, Lenarz, 2014 , Devocht, Janssen, Chalupper, Stokroos, George, 2016 , Ernst, Anton, Brendel, Battmer, 2019 , Vroegop, Homans, Goedegebure, Dingemanse, Immerzeel, van der Schroeff, 2018 , Weissgerber, Rader, Baumann, 2017 , Zedan, Jürgens, Williges, Kollmeier, Wiebe, Galindo, Wesarg, 2021 ). The simplest group of beamformers are monaural beamformers (i.e., implemented in a single hearing device) which use the signals of two or more microphones to reduce the noise on one side of the listener, e.g., only the HA side or only CI side ( Ernst et al., 2019 ).…”

“…Most CI and HA devices have monaural beamformers, including the ones used by bimodal CI users. Studies comparing the two types of beamformers with bimodal CI users showed that binaural beamformers outperform monaural beamformers, especially in complex acoustic scenes by about 2–4 dB additional SRT-benefit ( Ernst, Anton, Brendel, Battmer, 2019 , Zedan, Jürgens, Williges, Kollmeier, Wiebe, Galindo, Wesarg, 2021 ).…”

“…This impedes the understanding about the interaction that spatial noise reduction algorithms and bimodal CI listening has, because both signal processing and physiologic mechanisms are unknown. An exception is the data from Zedan et al. (2021) , who used open-access implementations of spatial noise processing algorithms within the Master Hearing Aid (MHA, Grimm et al.…”

“…Furthermore, the recruited bimodal CI users all were implanted on the right side and used the same CI speech processor and signal processing strategy, reducing confounds from ear-of-entry and coding strategies. In addition, reproducible, albeit realistic acoustic scenes were taken in Zedan et al. (2021) by using virtual acoustics and providing the signals to the CI and the HA contralaterally via direct audio input.…”

“…Their study can be seen as belonging to a series of studies using the same approach and preprocessing algorithms in bilateral CI users ( Baumgärtel et al., 2015a ), bilateral HA users and NH listeners ( Völker et al., 2015 ). Therefore, the experimental dataset with actual bimodal CI users by Zedan et al. (2021) provides a good basis to study the interaction between spatial noise algorithms and bimodal CI listening.…”