A loudness model with a central gain is suggested to improve individualized predictions of loudness scaling data from normal hearing and hearing impaired listeners. The current approach is based on the loudness model of Pieper [(2016). J. Acoust. Soc. Am., 2896], which simulated the nonlinear inner ear mechanics as transmission-line model in a physical and physiological plausible way. Individual hearing thresholds were simulated by a cochlear gain reduction in the transmission-line model and linear attenuation (damage of inner hair cells) prior to an internal threshold. This and similar approaches of current loudness models that characterize the individual hearing loss were shown to be insufficient to account for individual loudness perception, in particular at high stimulus levels close to the uncomfortable level. An additional parameter, termed "post gain," was introduced to improve upon the previous models. The post gain parameter amplifies the signal parts above the internal threshold and can better account for individual variations in the overall steepness of loudness functions and for variations in the uncomfortable level which are independent of the hearing loss. The post gain can be interpreted as a central gain occurring at higher stages as a result of peripheral deafferentation.
The perception of loudness is strongly influenced by peripheral auditory processing, which calls for a physiologically correct peripheral auditory processing stage when constructing advanced loudness models. Most loudness models, however, rather follow a functional approach: a parallel auditory filter bank combined with a compression stage, followed by spectral and temporal integration. Such classical loudness models do not allow to directly link physiological measurements like otoacoustic emissions to properties of their auditory filterbank. However, this can be achieved with physiologically motivated transmission-line models (TLMs) of the cochlea. Here two active and nonlinear TLMs were tested as the peripheral front end of a loudness model. The TLMs are followed by a simple generic back end which performs integration of basilar-membrane "excitation" across place and time to yield a loudness estimate. The proposed model approach reaches similar performance as other state-of-the-art loudness models regarding the prediction of loudness in sones, equal-loudness contours (including spectral fine structure), and loudness as a function of bandwidth. The suggested model provides a powerful tool to directly connect objective measures of basilar membrane compression, such as distortion product otoacoustic emissions, and loudness in future studies.
The individual loudness perception of a patient plays an important role in hearing aid satisfaction and use in daily life. Hearing aid fitting and development might benefit from individualized loudness models (ILMs), enabling better adaptation of the processing to individual needs. The central question is whether additional parameters are required for ILMs beyond non-linear cochlear gain loss and linear attenuation common to existing loudness models for the hearing impaired (HI). Here, loudness perception in eight normal hearing (NH) and eight HI listeners was measured in conditions ranging from monaural narrowband to binaural broadband, to systematically assess spectral and binaural loudness summation and their interdependence. A binaural summation stage was devised with empirical monaural loudness judgments serving as input. While NH showed binaural inhibition in line with the literature, binaural summation and its inter-subject variability were increased in HI, indicating the necessity for individualized binaural summation. Toward ILMs, a recent monaural loudness model was extended with the suggested binaural stage, and the number and type of additional parameters required to describe and to predict individual loudness were assessed. In addition to one parameter for the individual amount of binaural summation, a bandwidth-dependent monaural parameter was required to successfully account for individual spectral summation.
One consequence of sensorineural hearing loss is an altered loudness perception with a typically steeper progression of loudness as a function of stimulus level (loudness recruitment). Existing loudness models aim to explain altered loudness functions in hearing impaired (HI) effectively by means of an attenuation and compression component. Here the physiologically motivated loudness model of Pieper et al. [J. Acoust. Soc. Am. 139, 2896 (2016)] which simulates the nonlinear inner ear mechanics (transmission-line model, TLM) is used and extended to help distinguishing the role of peripheral factors, like damage to the outer hair cells (reduction of cochlear gain), and higher stages of auditory processing on loudness perception. Individual hearing thresholds were simulated by cochlear gain reduction in the TLM and linear attenuation (damage of inner hair cells) prior to an internal threshold. Hearing threshold and cochlear gain loss were estimated from individual loudness scaling data for narrowband noise. It was demonstrated that existing loudness models fail to predict individual loudness functions for HI. The current model showed better agreement with the data and accounted for individual loudness functions in HI and normal hearing using a linear weighting above the internal threshold (referred to as post gain).
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
customersupport@researchsolutions.com
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.