Speech intelligibility in noise varies widely across hearing aid users despite noise management features. Traditional approaches, such as adaptive beamforming and single-channel noise reduction, can reduce background noise but may introduce signal distortions that degrade speech intelligibility, particularly for listeners with poorer cognitive abilities. Newer deep neural network-based noise reduction (DNN) can potentially improve signal-to-noise ratio while minimizing distortions. This study aims to characterize how individual cognitive abilities influence outcomes with DNN relative to adaptive beamforming across acoustic scenes. Listeners with hearing loss completed sentence intelligibility tasks using wearable hearing aids programmed with adaptive beamforming and DNN. Target speech and competing maskers were presented from on- and off-axis locations in co-located and spatially separated configurations, with masker types including gender-matched two-talker speech or diffuse noise. Participants also completed a cognitive test battery assessing working memory, processing speed, and attention control. Results-to-date indicate that on average beamforming results in higher intelligibility with two-talker maskers, whereas DNN provides better intelligibility in diffuse noise and for off-axis targets, with large individual variability. The presentation will discuss how variability in intelligibility across these noise management strategies relates to individual cognitive profiles and susceptibility to signal distortions.
Varsha Rallapalli, Sophia Kreismer, Erol J. Ozmeral· Journal of the Acoustical So...· 0 citations
Speech perception with competing talkers can be a major challenge, especially for listeners with hearing loss. Listeners use auditory grouping cues to selectively attend to speech of interest and ignore the irrelevant signals, and recent work has shown that neural measures can reveal this ability to follow speech in complex acoustic environments. In most cases, prior studies have used research-grade, high-density electroencephalography (EEG) equipment to demonstrate this phenomenon; however, there are economic and clinical barriers for using these systems that may be overcome with open-source systems. The present study investigated the functional benefits and uses of low-density, dry EEG technology as an affordable and useful alternative to research-grade wet caps in neural speech tracking designs. This study was performed in normal hearing listeners with both systems for direct comparison. Experiment 1 looked at neural speech tracking in quiet, and experiment 2 investigated neural speech tracking with competing speech streams. The present study provides a comprehensive assessment of a research-grade system with wet electrodes compared to an open-source system with dry electrodes, which may provide clearer implications for future advancements in real-world application, such as “neuro-steered” hearing devices.
Zenzele Thomas, Erol J. Ozmeral· Journal of the Acoustical So...· 0 citations
Despite technical innovations in amplification and signal processing, hearing aid users still frequently report difficulty understanding speech in noise. Recent advances in hearing aid technology using deep neural networks (DNNs) promise to expand benefits of amplification beyond traditional noise reduction features. The present study evaluated the efficacy of a commercially available DNN-enabled hearing aid in a free-field speech understanding task using the coordinate response measure corpus with noise background. We compared multiple configurations of the DNN-enabled device (DNN-on versus DNN-off) as well as comparison devices with traditional noise reduction technologies. Results showed a significant benefit of the DNN-based noise reduction represented by higher CRM accuracy at all target locations, with the highest behavioral performance improvement observed at lateral target locations (±120 deg) for the DNN-enabled device compared to the same device with the DNN-off or the comparison devices. Furthermore, individual behavioral and cognitive measures were shown in some cases to have direct associations with this benefit. The results reported here demonstrate the benefits of unique noise reduction features to improve listener performance across multiple objective measures, and listener variability may in part be explained by suprathreshold and cognitive abilities.
Erol J. Ozmeral, Carrie A. Secor, Nathan C. Higgins· Journal of the Acoustical So...· 0 citations
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