Modeling Speech Intelligibility of Simulated Bimodal and Single-Sided Deaf Cochlear Implant Users

Zedan, Ayham; Williges, Ben; Jürgens, Tim

doi:10.3813/aaa.919256

Cited by 8 publications

(14 citation statements)

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“…intelligibility and an SNR-dependent bimodal benefit might simplify existing models, as they currently also take into account a binaural equalization-cancellation stage (Williges et al, 2015;Zedan et al, 2018).…”

Section: Discussionmentioning

confidence: 99%

Speech Understanding With Bimodal Stimulation Is Determined by Monaural Signal to Noise Ratios: No Binaural Cue Processing Involved

Dieudonné

Francart

2020

Ear &Amp; Hearing

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Objectives: To investigate the mechanisms behind binaural and spatial effects in speech understanding for bimodal cochlear implant listeners. In particular, to test our hypothesis that their speech understanding can be characterized by means of monaural signal-to-noise ratios, rather than complex binaural cue processing such as binaural unmasking. Design:We applied a semantic framework to characterize binaural and spatial effects in speech understanding on an extensive selection of the literature on bimodal listeners. In addition, we performed two experiments in which we measured speech understanding in different masker types(1) using head-related transfer functions, and (2) while adapting the broadband signal-to-noise ratios in both ears independently. We simulated bimodal hearing with a vocoder in one ear (the cochlear implant side) and a low pass filter in the other ear (the hearing aid side). By design, the cochlear implant side was the main contributor to speech understanding in our simulation. Results:We found that spatial release from masking can be explained as a simple trade-off between a monaural change in signal-to-noise at the cochlear implant side (quantified as the head shadow effect) and an opposite change in signal-to-noise at the hearing aid side (quantified as a change in bimodal benefit). In simulated bimodal listeners, we found that for every 1 dB increase in signalto-noise ratio at the hearing aid side, the bimodal benefit improved by approximately 0.4 dB in signal-to-noise ratio. Conclusions:Although complex binaural cue processing is often implicated when discussing speech intelligibility in adverse listening conditions, performance can simply be explained based on monaural signal-to-noise ratios for bimodal listeners.

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Section: Discussionmentioning

confidence: 99%

Speech Understanding With Bimodal Stimulation Is Determined by Monaural Signal to Noise Ratios: No Binaural Cue Processing Involved

Dieudonné

Francart

2020

Ear &Amp; Hearing

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“…This is known to affect localization ability in normal-hearing and bimodal CI users ( Zirn et al., 2019 ). Although the effect on speech-in-noise performance has, to the author’s knowledge, not been tested yet in bimodal CI users, significant effects are very unlikely, because the task-specific better-ear-listening in bimodal CI users ( Williges et al., 2019 ) does not require access to ITDs ( Zedan et al. 2018 ).…”

Section: Discussionmentioning

confidence: 99%

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

et al. 2021

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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.

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“…Furthermore, open tools may accelerate relevant studies with novel algorithms, lower the barriers for hardware and software development in research environments, facilitate collaborative research efforts and enable more reproducibility in hearing research. The open community platform for hearing aid algorithm research open Master Hearing Aid (openMHA, [ 2 , 3 ]) is such a tool, which has reached the level of maturity to be used in a wide research community for hearing device research and for studies with hearing impaired subjects [ 4 – 30 ], see Section 1.1 for an overview.…”

Section: Motivation and Significancementioning

confidence: 99%

“…Since its first release in 2017 openMHA is utilized in research related to hearing aids, evaluation of signal processing methods and for the setup of hearing aid processing in real-time systems. The software has been used for various purposes such as fitting of a multi-band dynamic range compressor to the hearing loss of hearing-impaired subjects a) in order to model speech intelligibility in cochlear implant users [ 4 ], predicting speech recognition performance in aided subjects [ 5 ] also including a directional microphone available with openMHA, and evaluation of near-end listening enhancement [ 6 ] with individual hearing loss compensation. In that context the openMHA fitting tool (see Fig.…”

Section: Motivation and Significancementioning

confidence: 99%

Open community platform for hearing aid algorithm research: open Master Hearing Aid (openMHA)

et al. 2022

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Modeling Speech Intelligibility of Simulated Bimodal and Single-Sided Deaf Cochlear Implant Users

Cited by 8 publications

References 0 publications

Speech Understanding With Bimodal Stimulation Is Determined by Monaural Signal to Noise Ratios: No Binaural Cue Processing Involved

Speech Understanding With Bimodal Stimulation Is Determined by Monaural Signal to Noise Ratios: No Binaural Cue Processing Involved

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

Open community platform for hearing aid algorithm research: open Master Hearing Aid (openMHA)

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