Contributions of Low- and High-Frequency Sensorineural Hearing Deficits to Speech Intelligibility in Noise

Abstract

This study investigates the role of hearing sensitivity, age and supra-threshold hearing to speech recognition in quiet, stationary, and modulated noise. Three participant groups were tested: young normal hearing (yNH), older normalhearing (oNH), and older hearing-impaired (oHI) listeners. The relative importance of near and supra-threshold hearing deficits was assessed in different frequency regions by measuring speech reception thresholds (SRTs) using broad- . CC-BY-NC-ND 4.0 International license It is made available under a (which was not peer-reviewed) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity.The copyright holder for this preprint . http://dx.doi.org/10.1101/358127 doi: bioRxiv preprint first posted online Jun. 29, 2018; present for BB, LP and HP conditions and related to the modulated (not stationary) SRT performance. (iv) Sensitivity to temporal-envelopes is important for HF masking release and SRTs in modulated noise, whereas spectral resolution is a better predictor of LF speech recognition in modulated noise. This study identified the role of near and supra-threshold cues in the perception of amplitude-modulation and speech-in-noise, and can steer the development of hearing-aid algorithms targeted to mediate supra-threshold hearing deficits.

The Speech Envelope Following Response in Normal and Hearing Impaired Listeners

“…The copyright holder for this preprint this version posted March 13, 2022. ; https://doi.org/10.1101/2022.03.12.484064 doi: bioRxiv preprint was fixed at 70 dB SPL and the difficulty was adjusted to by step-wise varying the noise level after each decision in a one-up one-down criterion, based on the sentence score (Wardenga et al, 2015). The test was repeated for filtered sentences (FIR filter with order 1024) of the original sentences, by either low pass filtering the sentences at 1500 Hz or high pass filtering them at 1650 Hz (as in Verhulst & Warzybok, 2018). The comparison was also made more frequency specific by evaluating the speech reception threshold (SRT) in quiet and in noise for filtered sentences, allowing to segregate important high frequency cues from low frequency cues of sounds.…”

Model-based hearing-enhancement strategies for cochlear synaptopathy pathologies

“…The Flemish Matrix includes 260 sentences recorded by a female speaker, each comprised of a 5-word combination from a closed set of 50 Flemish words. To generate the HP speech material, the (BB) Flemish Matrix sentences were HP filtered (zero-phase digital filtering) using an FIR filter with an order of 1024 and a cutoff frequency f cut = 1650 Hz (as in [70, 71]). Then, speech-shaped noise (SSN) material was generated from the long-term average speech spectrum of all sentences (as in [67]), separately for the BB and HP-filtered material.…”

“…To generalise the two processing types for different audio stimuli, we first focussed on high-pass (HP) filtered speech (i.e., speech content above f cut = 1.65 kHz) which relates more to the SAM stimuli. The intelligibility of HP-filtered speech relies on the coding of the temporal envelope of sound [68,69] and has been linked to the EFR results of listeners in previous CS-related studies [62,[70][71][72]. After establishing the envelope processing for HP-filtered speech and evaluating the simulated restoration that was achieved, the CS-compensating algorithms can be used in exactly the same way to process any stimulus.…”

Model-based hearing-enhancement strategies for cochlear synaptopathy pathologies

“…To generalise the two processing types for different audio stimuli, we first focussed on high-pass (HP) filtered speech (i.e., speech content above f cut = 1.65 kHz) which relates more to the SAM stimuli. The intelligibility of HP-filtered speech relies on the coding of the temporal envelope of sound [57,58] and has been linked to the EFR results of listeners in previous CS-related studies [52,59,60]. After establishing the envelope processing for HP-filtered speech and evaluating the simulated restoration that was achieved, the CS-compensating algorithms can be used in exactly the same way to process any stimulus.…”

“…The Flemish Matrix includes 260 sentences recorded by a female speaker, each comprised of a 5-word combination from a closed set of 50 Flemish words. To generate the HP speech material, the (BB) Flemish Matrix sentences were HP filtered (zero-phase digital filtering) using an FIR filter with an order of 1024 and a cutoff frequency f cut = 1650 Hz (as in [59,60]). Then, speech-shaped noise (SSN) material was generated from the long-term average speech spectrum of all sentences (as in [56]), separately for the BB and HP-filtered material.…”