Optimized loudness-function estimation for categorical loudness scaling data

Toward parametric Bayesian adaptive procedures for multi-frequency categorical loudness scaling

A series of Bayesian adaptive procedures to estimate loudness growth across a wide frequency range from individual listeners was developed, and these procedures were compared. Simulation experiments were conducted based on multinomial psychometric functions for categorical loudness scaling across ten test frequencies estimated from 61 listeners with normal hearing and 87 listeners with sensorineural hearing loss. Adaptive procedures that optimized the stimulus selection based on the interim estimates of two types of category-boundary models were tested. The first type of model was a phenomenological model of category boundaries adopted from previous research studies, while the other type was a data-driven model derived from a previously collected set of categorical loudness scaling data. An adaptive procedure without Bayesian active learning was also implemented. Results showed that all adaptive procedures provided convergent estimates of the loudness category boundaries and equal-loudness contours between 250 and 8000 Hz. Performing post hoc model fitting, using the data-driven model, on the collected data led to satisfactory accuracies, such that all adaptive procedures tested in the current study, independent of modeling approach and stimulus-selection rules, were able to provide estimates of the equal-loudness-level contours between 20 and 100 phons with root-mean-square errors typically under 6 dB after 100 trials.

Development and Evaluation of a Loudness Validation Method With Natural Signals for Hearing Aid Fitting

Loudness is a fundamental dimension of auditory perception. When hearing impairment results in a loudness deficit, hearing aids are typically prescribed to compensate for this. However, the relationship between an individual's specific hearing impairment and the hearing aid fitting strategy used to address it is usually not straightforward. Various iterations of fine-tuning and troubleshooting by the hearing care professional are required, based largely on experience and the introspective feedback from the hearing aid user. We present the development of a new method for validating an individual's loudness perception of natural signals relative to a normal-hearing reference. It is a measurement method specifically designed for the situation typically encountered by hearing care professionals, namely, with hearing-impaired individuals in the free field with their hearing aids in place. In combination with the qualitative user feedback that the measurement is fast and that its results are intuitively displayed and easily interpretable, the method fills a gap between existing tools and is well suited to provide concrete guidance and orientation to the hearing care professional in the process of individual gain adjustment.

Predicting Aided Outcome With Aided Word Recognition Scores Measured With Linear Amplification at Above-conversational Levels

OBJECTIVES

Many hearing aid (HA) users receive limited benefit from amplification, especially when trying to understand speech in noise, and they often report hearing-related residual activity limitations. Current HA fitting strategies are typically based on pure-tone hearing thresholds only, even though suprathreshold factors have been linked to aided outcomes. Furthermore, clinical measures of speech perception such as word recognition scores (WRSs) are performed without frequency-specific amplification, likely resulting in suboptimal speech audibility and thus inaccurate estimates of suprathreshold hearing abilities. Corresponding measures with frequency-specific amplification ("aided") would likely improve such estimates and enable more accurate aided outcome prediction. Here, we investigated potential links between either unaided WRSs or aided WRSs measured at several above-conversational levels and two established HA outcome measures: The Hearing-In-Noise Test (HINT) and the International Outcome Inventory for Hearing Aids (IOI-HA).

DESIGN

Thirty-seven older individuals with bilateral hearing impairments participated. Two conditions were tested: unaided and aided, with all stimuli presented over headphones. In the unaided condition, the most comfortable level (MCL) for the presented speech stimuli, WRS at MCL+10 dB as well as uncomfortable levels (UCLs) for narrowband noise stimuli were measured. In the aided condition, all stimuli were individually amplified according to the "National Acoustic Laboratories-Revised, Profound" fitting rule. Aided WRSs were then measured using an Interacoustics Affinity system at three above-conversational levels, allowing for the maximum aided WRS as well as the presence of "rollover" in the performance-intensity function to be estimated. Multivariate data analyses were performed to examine the relations between the HINT (measured using a simulated HA with the NAL-RP amplification) or IOI-HA scores (for the participants' own HAs) and various potential predictors (age, pure-tone average hearing loss, unaided WRS, aided WRS, rollover presence [ROp], and UCL).

RESULTS

Aided WRSs predicted the HINT scores better than any other predictor and were also the only significant predictor of the IOI-HA scores. In addition, UCL and ROp in the aided WRSs were significant predictors of the HINT scores and competed for variance in the statistical models. Neither age nor pure-tone average hearing loss could predict the two aided outcomes.

CONCLUSIONS

Aided WRSs can predict HA outcome more effectively than unaided WRSs, age or pure-tone audiometry and could be relatively easily implemented in clinical settings. More research is necessary to better understand the relations between ROp, UCL and speech recognition at above-conversational levels.

Assessing and Modeling Spatial Release From Listening Effort in Listeners With Normal Hearing: Reference Ranges and Effects of Noise Direction and Age

Listening to speech in noisy environments is challenging and effortful. Factors like the signal-to-noise ratio (SNR), the spatial separation between target speech and noise interferer(s), and possibly also the listener's age might influence perceived listening effort (LE). This study measured and modeled the effect of the spatial separation of target speech and interfering stationary speech-shaped noise on the perceived LE and its relation to the age of the listeners. Reference ranges for the relationship between subjectively perceived LE and SNR for different noise azimuths were established. For this purpose, 70 listeners with normal hearing and from three age groups rated the perceived LE using the Adaptive Categorical Listening Effort Scaling method (ACALES, Krueger et al., 2017a) with speech from the front and noise from 0°, 90°, 135°, or 180° azimuth. Based on these data, the spatial release from listening effort (SRLE) was calculated. The noise azimuth had a strong effect on SRLE, with the highest release for 135°. The binaural speech intelligibility model (BSIM2020, Hauth et al., 2020) predicted SRLE very well at negative SNRs, but overestimated for positive SNRs. No significant effect of age was found on the respective subjective ratings. Therefore, the reference ranges were determined independently of age. These reference ranges can be used for the classification of LE measurements. However, when the increase of the perceived LE with SNR was analyzed, a significant age difference was found between the listeners of the youngest and oldest group when considering the upper range of the LE function.

Spectral and binaural loudness summation of equally loud narrowband signals in single-sided-deafness and bilateral cochlear implant users

Recent studies on loudness perception of binaural broadband signals in hearing impaired listeners found large individual differences, suggesting the use of such signals in hearing aid fitting. Likewise, clinical cochlear implant (CI) fitting with narrowband/single-electrode signals might cause suboptimal loudness perception in bilateral and bimodal CI listeners. Here spectral and binaural loudness summation in normal hearing (NH) listeners, bilateral CI (biCI) users, and unilateral CI (uCI) users with normal hearing in the unaided ear was investigated to assess the relevance of binaural/bilateral fitting in CI users. To compare the three groups, categorical loudness scaling was performed for an equal categorical loudness noise (ECLN) consisting of the sum of six spectrally separated third-octave noises at equal loudness. The acoustical ECLN procedure was adapted to an equivalent procedure in the electrical domain using direct stimulation. To ensure the same broadband loudness in binaural measurements with simultaneous electrical and acoustical stimulation, a modified binaural ECLN was introduced and cross validated with self-adjusted loudness in a loudness balancing experiment. Results showed a higher (spectral) loudness summation of the six equally loud narrowband signals in the ECLN in CI compared to NH. Binaural loudness summation was found for all three listener groups (NH, uCI, and biCI). No increased binaural loudness summation could be found for the current uCI and biCI listeners compared to the NH group. In uCI loudness balancing between narrowband signals and single electrodes did not automatically result in a balanced loudness perception across ears, emphasizing the importance of binaural/bilateral fitting.

Conformities and gaps of clinical audiological data with the international classification of functioning disability and health core sets for hearing loss

OBJECTIVE

The International Classification of Functioning Disability and Health (ICF) is a classification of health and health-related domains created by the World Health Organization and can be used as a standard to evaluate the health and disability of individuals. The ICF Core Set for Hearing Loss (CSHL) refers to the ICF categories found to be relative to Hearing Loss (HL) and the consequences of it on daily life. This study aimed to adapt the content of a database gathered in Hörzentrum Oldenburg gGmbH that included HL medical assessments and audiological data to the ICF.

DESIGN

ICF linking rules were applied to these assessment methods including medical interviews, ear examinations, pure-tone audiometry, Adaptive Categorical Loudness Scaling, and speech intelligibility test.

STUDY SAMPLE

1316 subjects.

RESULTS

In total, 44% of the brief and 18% of the comprehensive CSHL categories were addressed. The hearing functions were broadly evaluated. "Activities and Participation" and "Environmental Factors" were poorly examined (17% and 12% of the comprehensive CSHL categories, respectively).

CONCLUSIONS

The HL correlation with day-to-day activities limitation, performance restriction, and environmental conditions were poorly addressed. This study showed the essence of incorporating these methodologies with approaches that assess the daily-life challenges caused by HL in rehabilitation.

Evaluation of Remote Categorical Loudness Scaling

PURPOSE

The aims of this study were to (a) demonstrate the feasibility of administering categorical loudness scaling (CLS) tests in a remote setting, (b) assess the reliability of remote compared with laboratory CLS results, and (c) provide preliminary evidence of the validity of remote CLS testing.

METHOD

CLS data from 21 adult participants collected in a home setting were compared to CLS data collected in a laboratory setting from previous studies. Five participants took part in studies in both settings. Precalibrated equipment was delivered to participants who performed headphone output level checks and measured ambient noise levels. After a practice run, CLS measurements were collected for two runs at 1 and 4 kHz.

RESULTS

Mean headphone output levels were within 1.5 dB of the target calibration level. Mean ambient noise levels were below the target level. Within-run variability was similar between the two settings, but across-run bias was smaller for data collected in the laboratory setting compared with the remote setting. Systematic differences in CLS functions were not observed for the five individuals who participated in both settings.

CONCLUSIONS

This study demonstrated that precise stimulus levels can be delivered and background noise levels can be controlled in a home environment. Across-run bias for remote CLS was larger than for in-laboratory CLS, indicating that further work is needed to improve the reliability of CLS data collected in remote settings. Supplemental Material https://doi.org/10.23641/asha.17131856.

Interpretable Clinical Decision Support System for Audiology Based on Predicted Common Audiological Functional Parameters (CAFPAs)

Common Audiological Functional Parameters (CAFPAs) were previously introduced as abstract, measurement-independent representation of audiological knowledge, and expert-estimated CAFPAs were shown to be applicable as an interpretable intermediate layer in a clinical decision support system (CDSS). Prediction models for CAFPAs were built based on expert knowledge and one audiological database to allow for data-driven estimation of CAFPAs for new, individual patients for whom no expert-estimated CAFPAs are available. Based on the combination of these components, the current study explores the feasibility of constructing a CDSS which is as interpretable as expert knowledge-based classification and as data-driven as machine learning-based classification. To test this hypothesis, the current study investigated the equivalence in performance of predicted CAFPAs compared to expert-estimated CAFPAs in an audiological classification task, analyzed the importance of different CAFPAs for high and comparable performance, and derived explanations for differences in classified categories. Results show that the combination of predicted CAFPAs and statistical classification enables to build an interpretable but data-driven CDSS. The classification provides good accuracy, with most categories being correctly classified, while some confusions can be explained by the properties of the employed database. This could be improved by including additional databases in the CDSS, which is possible within the presented framework.

Revisiting Auditory Profiling: Can Cognitive Factors Improve the Prediction of Aided Speech-in-Noise Outcome?

Hearing aids (HA) are the most common type of rehabilitation treatment for age-related hearing loss. However, HA users often obtain limited benefit from their devices, particularly in noisy environments, and thus many HA candidates do not use them at all. A possible reason for this could be that current HA fittings are audiogram-based, that is, they neglect supra-threshold factors. In an earlier study, an auditory-profiling method was proposed as a basis for more personalized HA fittings. This method classifies HA users into four profiles that differ in terms of hearing sensitivity and supra-threshold hearing abilities. Previously, HA users belonging to these profiles showed significant differences in terms of speech recognition in noise but not subjective assessments of speech-in-noise (SIN) outcome. Moreover, large individual differences within some profiles were observed. The current study therefore explored if cognitive factors can help explain these differences and improve aided outcome prediction. Thirty-nine older HA users completed sets of auditory and SIN tests as well as two tablet-based cognitive measures (the Corsi block-tapping and trail-making tests). Principal component analyses were applied to extract the dominant sources of variance both within individual tests producing many variables and within the three types of tests. Multiple linear regression analyses performed on the extracted components showed that auditory factors were related to aided speech recognition in noise but not to subjective SIN outcome. Cognitive factors were unrelated to aided SIN outcome. Overall, these findings provide limited support for adding those two cognitive tests to the profiling of HA users.

Predicting Common Audiological Functional Parameters (CAFPAs) as Interpretable Intermediate Representation in a Clinical Decision-Support System for Audiology

The application of machine learning for the development of clinical decision-support systems in audiology provides the potential to improve the objectivity and precision of clinical experts' diagnostic decisions. However, for successful clinical application, such a tool needs to be accurate, as well as accepted and trusted by physicians. In the field of audiology, large amounts of patients' data are being measured, but these are distributed over local clinical databases and are heterogeneous with respect to the applied assessment tools. For the purpose of integrating across different databases, the Common Audiological Functional Parameters (CAFPAs) were recently established as abstract representations of the contained audiological information describing relevant functional aspects of the human auditory system. As an intermediate layer in a clinical decision-support system for audiology, the CAFPAs aim at maintaining interpretability to the potential users. Thus far, the CAFPAs were derived by experts from audiological measures. For designing a clinical decision-support system, in a next step the CAFPAs need to be automatically derived from available data of individual patients. Therefore, the present study aims at predicting the expert generated CAFPA labels using three different machine learning models, namely the lasso regression, elastic nets, and random forests. Furthermore, the importance of different audiological measures for the prediction of specific CAFPAs is examined and interpreted. The trained models are then used to predict CAFPAs for unlabeled data not seen by experts. Prediction of unlabeled cases is evaluated by means of model-based clustering methods. Results indicate an adequate prediction of the ten distinct CAFPAs. All models perform comparably and turn out to be suitable choices for the prediction of CAFPAs. They also generalize well to unlabeled data. Additionally, the extracted relevant features are plausible for the respective CAFPAs, facilitating interpretability of the predictions. Based on the trained models, a prototype of a clinical decision-support system in audiology can be implemented and extended towards clinical databases in the future.

Relation between hearing abilities and preferred playback settings for speech perception in complex listening conditions

OBJECTIVE

This study investigated if individual preferences with respect to the trade-off between a good signal-to-noise ratio and a distortion-free speech target were stable across different masking conditions and if simple adjustment methods could be used to identify subjects as either "noise haters" or "distortions haters".

DESIGN

In each masking condition, subjects could adjust the target speech level according to their preferences by employing (i) linear gain or gain at the cost of (ii) clipping distortions or (iii) compression distortions. The comparison of these processing conditions allowed investigating the preferred trade-off between distortions and noise disturbance.

STUDY SAMPLE

Thirty subjects differing widely in hearing status (normal-hearing to moderately impaired) and age (23-85 years).

RESULTS

High test-retest stability of individual preferences was found for all modification schemes. The preference adjustments suggested that subjects could be consistently categorised along a scale from "noise haters" to "distortion haters", and this preference trait remained stable through all maskers, spatial conditions, and types of distortions.

CONCLUSIONS

Employing quick self-adjustment to collect listening preferences in complex listening conditions revealed a stable preference trait along the "noise vs. distortions" tolerance dimension. This could potentially help in fitting modern hearing aid algorithms to the individual user.

Auditory Tests for Characterizing Hearing Deficits in Listeners With Various Hearing Abilities: The BEAR Test Battery

The Better hEAring Rehabilitation (BEAR) project aims to provide a new clinical profiling tool-a test battery-for hearing loss characterization. Although the loss of sensitivity can be efficiently measured using pure-tone audiometry, the assessment of supra-threshold hearing deficits remains a challenge. In contrast to the classical "attenuation-distortion" model, the proposed BEAR approach is based on the hypothesis that the hearing abilities of a given listener can be characterized along two dimensions, reflecting independent types of perceptual deficits (distortions). A data-driven approach provided evidence for the existence of different auditory profiles with different degrees of distortions. Ten tests were included in a test battery, based on their clinical feasibility, time efficiency, and related evidence from the literature. The tests were divided into six categories: audibility, speech perception, binaural processing abilities, loudness perception, spectro-temporal modulation sensitivity, and spectro-temporal resolution. Seventy-five listeners with symmetric, mild-to-severe sensorineural hearing loss were selected from a clinical population. The analysis of the results showed interrelations among outcomes related to high-frequency processing and outcome measures related to low-frequency processing abilities. The results showed the ability of the tests to reveal differences among individuals and their potential use in clinical settings.

Toward an Individual Binaural Loudness Model for Hearing Aid Fitting and Development

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.

Maximum Expected Information Approach for Improving Efficiency of Categorical Loudness Scaling

Categorical loudness scaling (CLS) measures provide useful information about an individual's loudness perception across the dynamic range of hearing. A probability model of CLS categories has previously been described as a multi-category psychometric function (MCPF). In the study, a representative "catalog" of potential listener MCPFs was used in conjunction with maximum-likelihood estimation to derive CLS functions for participants with normal hearing and with hearing loss. The approach of estimating MCPFs for each listener has the potential to improve the accuracy of the CLS measurements, particularly when a relatively low number of data points are available. The present study extends the MCPF approach by using Bayesian inference to select stimulus parameters that are predicted to yield maximum expected information (MEI) during data collection. The accuracy and reliability of the MCPF-MEI approach were compared to the standardized CLS measurement procedure (ISO 16832:2006, 2006). A non-adaptive, fixed-level, paradigm served as a "gold-standard" for this comparison. The test time required to obtain measurements in the standard procedure is a major barrier to its clinical uptake. Test time was reduced from approximately 15 min to approximately 3 min with the MEI-adaptive procedure. Results indicated that the test-retest reliability and accuracy of the MCPF-MEI adaptive procedures were similar to the standardized CLS procedure. Computer simulations suggest that the reliability and accuracy of the MEI procedure were limited by intrinsic uncertainty of the listeners represented in the MCPF catalog. In other words, the MCPF provided insufficient predictive power to significantly improve adaptive-tracking efficiency under practical conditions. Concurrent optimization of both the MCPF catalog and the MEI-adaptive procedure have the potential to produce better results. Regardless of the adaptive-tracking method used in the CLS procedure, the MCPF catalog remains clinically useful for enabling maximum-likelihood determination of loudness categories.

Uni- and bilateral spectral loudness summation and binaural loudness summation with loudness matching and categorical loudness scaling

OBJECTIVE

Current hearing aid prescription rules assume that spectral loudness summation decreases with hearing impairment and that binaural loudness summation is independent of hearing loss and signal bandwidth. Previous studies have shown that these assumptions might be incorrect. Spectral loudness summation was measured and compared for loudness scaling and loudness matching.

DESIGN

In this study, the effect of bandwidth on binaural summation was investigated by comparing loudness perception of low-pass filtered, high-pass filtered, and broadband pink noise at 35 Categorical Units for both unilateral and bilateral presentation.

STUDY SAMPLE

Sixteen hearing-impaired listeners.

RESULTS

The results show that loudness differences between the three signals are different for bilateral presentation than for unilateral presentation. In specific, binaural loudness summation is larger for the low-pass filtered pink noise than for the high-pass filtered pink noise. Finally, individual variability in loudness perception near loudness discomfort level was found to be very large.

CONCLUSIONS

Loudness matching is offered as a fast and reliable method to measure individual loudness perception. As discomfort with loud sounds is one of the major problems encountered by hearing aid users, measurement of individual loudness perception could improve hearing aid fitting substantially.

Sensitivity and specificity of automatic audiological classification using expert-labelled audiological data and Common Audiological Functional Parameters

OBJECTIVE

As a step towards the development of an audiological diagnostic supporting tool employing machine learning methods, this article aims at evaluating the classification performance of different audiological measures as well as Common Audiological Functional Parameters (CAFPAs). CAFPAs are designed to integrate different clinical databases and provide abstract representations of measures.

DESIGN

Classification and evaluation of classification performance in terms of sensitivity and specificity are performed on a data set from a previous study, where statistical models of diagnostic cases were estimated from expert-labelled data.

STUDY SAMPLE

The data set contains 287 cases.

RESULTS

The classification performance in clinically relevant comparison sets of two competing categories was analysed for audiological measures and CAFPAs. It was found that for different audiological diagnostic questions a combination of measures using different weights of the parameters is useful. A set of four to six measures was already sufficient to achieve maximum classification performance which indicates that the measures contain redundant information.

CONCLUSIONS

The current set of CAFPAs was confirmed to yield in most cases approximately the same classification performance as the respective optimum set of audiological measures. Overall, the concept of CAFPAs as compact, abstract representation of auditory deficiencies is confirmed.

Can You Hear Out the Melody? Testing Musical Scene Perception in Young Normal-Hearing and Older Hearing-Impaired Listeners

It is well known that hearing loss compromises auditory scene analysis abilities, as is usually manifested in difficulties of understanding speech in noise. Remarkably little is known about auditory scene analysis of hearing-impaired (HI) listeners when it comes to musical sounds. Specifically, it is unclear to which extent HI listeners are able to hear out a melody or an instrument from a musical mixture. Here, we tested a group of younger normal-hearing (yNH) and older HI (oHI) listeners with moderate hearing loss in their ability to match short melodies and instruments presented as part of mixtures. Four-tone sequences were used in conjunction with a simple musical accompaniment that acted as a masker (cello/piano dyads or spectrally matched noise). In each trial, a signal-masker mixture was presented, followed by two different versions of the signal alone. Listeners indicated which signal version was part of the mixture. Signal versions differed either in terms of the sequential order of the pitch sequence or in terms of timbre (flute vs. trumpet). Signal-to-masker thresholds were measured by varying the signal presentation level in an adaptive two-down/one-up procedure. We observed that thresholds of oHI listeners were elevated by on average 10 dB compared with that of yNH listeners. In contrast to yNH listeners, oHI listeners did not show evidence of listening in dips of the masker. Musical training of participants was associated with a lowering of thresholds. These results may indicate detrimental effects of hearing loss on central aspects of musical scene perception.

Potential Consequences of Spectral and Binaural Loudness Summation for Bilateral Hearing Aid Fitting

Aversiveness of loud sounds is a frequent complaint by hearing aid users, especially when fitted bilaterally. This study investigates whether loudness summation can be held responsible for this finding. Two aspects of loudness summation should be taken into account: spectral loudness summation for broadband signals and binaural loudness summation for signals that are presented binaurally. In this study, the effect of different symmetrical hearing losses was studied. Measurements were obtained with the widely used technique of Adaptive Categorical Loudness Scaling. For large bandwidths, spectral loudness summation for hearing-impaired listeners was found to be greater than that for normal-hearing listeners, both for monaurally and binaurally presented signals. For binaural loudness summation, the effect of hearing loss was not significant. In all cases, individual differences were substantial.

Using Thresholds in Noise to Identify Hidden Hearing Loss in Humans

OBJECTIVES

Recent animal studies suggest that noise-induced synaptopathy may underlie a phenomenon that has been labeled hidden hearing loss (HHL). Noise exposure preferentially damages low spontaneous-rate auditory nerve fibers, which are involved in the processing of moderate- to high-level sounds and are more resistant to masking by background noise. Therefore, the effect of synaptopathy may be more evident in suprathreshold measures of auditory function, especially in the presence of background noise. The purpose of this study was to develop a statistical model for estimating HHL in humans using thresholds in noise as the outcome variable and measures that reflect the integrity of sites along the auditory pathway as explanatory variables. Our working hypothesis is that HHL is evident in the portion of the variance observed in thresholds in noise that is not dependent on thresholds in quiet, because this residual variance retains statistical dependence on other measures of suprathreshold function.

DESIGN

Study participants included 13 adults with normal hearing (≤15 dB HL) and 20 adults with normal hearing at 1 kHz and sensorineural hearing loss at 4 kHz (>15 dB HL). Thresholds in noise were measured, and the residual of the correlation between thresholds in noise and thresholds in quiet, which we refer to as thresholds-in-noise residual, was used as the outcome measure for the model. Explanatory measures were as follows: (1) auditory brainstem response (ABR) waves I and V amplitudes; (2) electrocochleographic action potential and summating potential amplitudes; (3) distortion product otoacoustic emissions level; and (4) categorical loudness scaling. All measurements were made at two frequencies (1 and 4 kHz). ABR and electrocochleographic measurements were made at 80 and 100 dB peak equivalent sound pressure level, while wider ranges of levels were tested during distortion product otoacoustic emission and categorical loudness scaling measurements. A model relating the thresholds-in-noise residual and the explanatory measures was created using multiple linear regression analysis.

RESULTS

Predictions of thresholds-in-noise residual using the model accounted for 61% (p < 0.01) and 48% (p < 0.01) of the variance in the measured thresholds-in-noise residual at 1 and 4 kHz, respectively.

CONCLUSIONS

Measures of thresholds in noise, the summating potential to action potential ratio, and ABR waves I and V amplitudes may be useful for the prediction of HHL in humans. With further development, our approach of quantifying HHL by the variance that remains in suprathreshold measures of auditory function after removing the variance due to thresholds in quiet, together with our statistical modeling, may provide a quantifiable and verifiable estimate of HHL in humans with normal hearing and with hearing loss. The current results are consistent with the view that inner hair cell and auditory nerve pathology may underlie suprathreshold auditory performance.

Physiologically motivated individual loudness model for normal hearing and hearing impaired listeners

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 et al. [(2016). J. Acoust. Soc. Am. 139, 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.

Loudness Perception of Pure Tones in Parkinson's Disease

PURPOSE

Reduced intensity is a hallmark of speech production in Parkinson's disease (PD). Previous work has examined the perception of intensity in PD to explain these speech deficits. This study reports loudness ratings of pure tones by individuals with PD and controls, all with normal thesholds for older adults.

METHOD

Twenty individuals with PD and 23 age- and sex-matched controls rated the loudness of pure tones from 1 (very soft) to 7 (uncomfortably loud). Tones at 500, 750, 1000, 2000, and 4000 Hz were presented from 35 to 80 dB HL (or until a rating of 7 was given). A mixed-model analysis of variance was performed on ratings to assess the effects of group, frequency, sound intensity, and ear. Loudness growth slopes were determined for each participant and analyzed by group.

RESULTS

The mean loudness growth slopes of the control and PD groups did not significantly differ.

CONCLUSIONS

No difference was found in loudness growth slopes in response to externally generated tones in PD. This is in contrast with the findings of previous studies of self-generated speech and externally presented speech. The underlying causes for impaired perception and production of loudness in PD require further investigation.

Comparison between adaptive and adjustment procedures for binaural loudness balancing

Binaural loudness balancing is performed in research and clinical practice when fitting bilateral hearing devices, and is particularly important for bimodal listeners, who have a bilateral combination of a hearing aid and a cochlear implant. In this study, two psychophysical binaural loudness balancing procedures were compared. Two experiments were carried out. In the first experiment, the effect of procedure (adaptive or adjustment) on the balanced loudness levels was investigated using noise band stimuli, of which some had a frequency shift to simulate bimodal hearing. In the second experiment, the adjustment procedure was extended. The effect of the starting level of the adjustment procedure was investigated and the two procedures were again compared for different reference levels and carrier frequencies. Fourteen normal hearing volunteers participated in the first experiment, and 38 in the second experiment. Although the final averaged loudness balanced levels of both procedures were similar, the adjustment procedure yielded smaller standard deviations across four test sessions. The results of experiment 2 demonstrated that in order to avoid bias, the adjustment procedure should be conducted twice, once starting from below and once from above the expected balanced loudness level.

Deriving loudness growth functions from categorical loudness scaling data

The goal of this study was to reconcile the differences between measures of loudness obtained with continuous, unbounded scaling procedures, such as magnitude estimation and production, and those obtained using a limited number of discrete categories, such as categorical loudness scaling (CLS). The former procedures yield data with ratio properties, but some listeners find it difficult to generate numbers proportional to loudness and the numbers cannot be compared across listeners to explore individual differences. CLS, where listeners rate loudness on a verbal scale, is an easier task, but the numerical values or categorical units (CUs) assigned to the points on the scale are not proportional to loudness. Sufficient CLS data are now available to assign values in sones, a scale proportional to loudness, to the loudness categories. As a demonstration of this approach, data from Heeren, Hohmann, Appell, and Verhey [J. Acoust. Soc. Am. 133, EL314-EL319 (2013)] were used to develop a CUsone metric, whose values were then substituted for the original CU values in reanalysis of a large set of CLS data obtained by Rasetshwane, Trevino, Gombert, Liebig-Trehearn, Kopun, Jesteadt, Neely, and Gorga [J. Acoust. Soc. Am. 137, 1899-1913 (2015)]. The resulting data are well fitted by power functions and are in general agreement with previously published results obtained with magnitude estimation, magnitude production, and cross modality matching.

Relation Between Listening Effort and Speech Intelligibility in Noise

PURPOSE

Subjective ratings of listening effort might be applicable to estimate hearing difficulties at positive signal-to-noise ratios (SNRs) at which speech intelligibility scores are near 100%. Hence, ratings of listening effort were compared with speech intelligibility scores at different SNRs, and the benefit of hearing aids was evaluated.

METHOD

Two groups of listeners, 1 with normal hearing and 1 with hearing impairment, performed adaptive speech intelligibility and adaptive listening effort tests (Adaptive Categorical Listening Effort Scaling; Krueger, Schulte, Brand, & Holube, 2017) with sentences of the Oldenburg Sentence Test (Wagener, Brand, & Kollmeier, 1999a, 1999b; Wagener, Kühnel, & Kollmeier, 1999) in 4 different maskers. Model functions were fitted to the data to estimate the speech reception threshold and listening effort ratings for extreme effort and no effort.

RESULTS

Listeners with hearing impairment showed higher rated listening effort compared with listeners with normal hearing. For listeners with hearing impairment, the rating extreme effort, which corresponds to negative SNRs, was more correlated to the speech reception threshold than the rating no effort, which corresponds to positive SNRs. A benefit of hearing aids on speech intelligibility was only verifiable at negative SNRs, whereas the effect on listening effort showed high individual differences mainly at positive SNRs.

CONCLUSION

The adaptive procedure for rating subjective listening effort yields information beyond using speech intelligibility to estimate hearing difficulties and to evaluate hearing aids.

Loudness summation of equal loud narrowband signals in normal-hearing and hearing-impaired listeners

OBJECTIVE

Loudness perception of binaural broadband signals, e.g. speech shaped noise, shows large individual differences using frequency-dependent amplification which was adjusted to restore the loudness perception of monaural narrowband signals in hearing-impaired (HI) listeners. To better understand and quantify this highly individual effect, loudness perception of broadband stimuli consisting of a number of spectrally separated narrowband components which where individually adjusted to equal loudness is of interest.

DESIGN

Based on categorical loudness scaling, the loudness of an equal categorical loudness noise (ECLN) consisting of six third-octave noises was assessed. For loudness categories "medium" und "very loud" the required narrowband loudness was analysed.

STUDY SAMPLE

Nine normal-hearing (NH) and ten HI listeners.

RESULTS

HI listeners showed lower narrowband loudness values compared to NH listeners, indicating an increased spectral loudness summation. More than 50% of the HI listeners showed higher binaural spectral loudness summation compared to NH listeners. The amount of binaural spectral loudness summation was highly correlated (r² = 0.92) with the loudness level at "very loud" of aided speech shaped noise.

CONCLUSIONS

The suggested ECLN measurement is suited to assess individual (binaural) broadband loudness in aided conditions, providing valuable information for hearing-aid fitting.

Development of an adaptive scaling method for subjective listening effort

An adaptive procedure for controlling the signal-to-noise ratio (SNR) when rating the subjectively perceived listening effort (Adaptive Categorical Listening Effort Scaling) is described. For this, the listening effort is rated on a categorical scale with 14 steps after the presentation of three sentences in a background masker. In a first phase of the procedure, the individual SNR range for ratings from "no effort" to "extreme effort" is estimated. In the following phases, stimuli with randomly selected SNRs within this range are presented. One or two linear regression lines are fitted to the data describing subjective listening effort as a function of SNR. The results of the adaptive procedure are independent of the initial SNR. Although a static procedure using fixed, predefined SNRs produced similar results, the adaptive procedure avoided lengthy pretests for suitable SNRs and limited possible bias in the rating procedures. The adaptive procedure resolves individual differences, as well as differences between maskers. Inter-individual standard deviations are about three times as large as intra-individual standard deviations and the intra-class correlation coefficient for test-retest reliability is, on average, 0.9.

Auditory and Non-Auditory Contributions for Unaided Speech Recognition in Noise as a Function of Hearing Aid Use

Differences in understanding speech in noise among hearing-impaired individuals cannot be explained entirely by hearing thresholds alone, suggesting the contribution of other factors beyond standard auditory ones as derived from the audiogram. This paper reports two analyses addressing individual differences in the explanation of unaided speech-in-noise performance among n = 438 elderly hearing-impaired listeners (mean = 71.1 ± 5.8 years). The main analysis was designed to identify clinically relevant auditory and non-auditory measures for speech-in-noise prediction using auditory (audiogram, categorical loudness scaling) and cognitive tests (verbal-intelligence test, screening test of dementia), as well as questionnaires assessing various self-reported measures (health status, socio-economic status, and subjective hearing problems). Using stepwise linear regression analysis, 62% of the variance in unaided speech-in-noise performance was explained, with measures Pure-tone average (PTA), Age, and Verbal intelligence emerging as the three most important predictors. In the complementary analysis, those individuals with the same hearing loss profile were separated into hearing aid users (HAU) and non-users (NU), and were then compared regarding potential differences in the test measures and in explaining unaided speech-in-noise recognition. The groupwise comparisons revealed significant differences in auditory measures and self-reported subjective hearing problems, while no differences in the cognitive domain were found. Furthermore, groupwise regression analyses revealed that Verbal intelligence had a predictive value in both groups, whereas Age and PTA only emerged significant in the group of hearing aid NU.

Development of a multi-category psychometric function to model categorical loudness measurements

A multi-category psychometric function (MCPF) is introduced for modeling the stimulus-level dependence of perceptual categorical probability distributions. The MCPF is described in the context of individual-listener categorical loudness scaling (CLS) data. During a CLS task, listeners select the loudness category that best corresponds to their perception of the presented stimulus. In this study, CLS MCPF results are reported for 37 listeners (15 normal hearing, 22 with hearing loss). Individual-listener MCPFs were parameterized, and a principal component analysis (PCA) was used to identify sources of inter-subject variability and reduce the dimensionality of the data. A representative "catalog" of potential listener MCPFs was created from the PCA results. A method is introduced for using the MCPF catalog and maximum-likelihood estimation, together, to derive CLS functions for additional participants; this technique improved the accuracy of the CLS results and provided a MCPF model for each listener. Such a technique is particularly beneficial when a relatively low number of measurements are available (e.g., International Standards Organization adaptive-level CLS testing). In general, the MCPF is a flexible tool that can characterize any type of ordinal, level-dependent categorical data. For CLS, the MCPF quantifies the suprathreshold variability across listeners and provides a model for probability-based analyses and methods.

The representation of level and loudness in the central auditory system for unilateral stimulation

Loudness is the perceptual correlate of the physical intensity of a sound. However, loudness judgments depend on a variety of other variables and can vary considerably between individual listeners. While functional magnetic resonance imaging (fMRI) has been extensively used to characterize the neural representation of physical sound intensity in the human auditory system, only few studies have also investigated brain activity in relation to individual loudness. The physiological correlate of loudness perception is not yet fully understood. The present study systematically explored the interrelation of sound pressure level, ear of entry, individual loudness judgments, and fMRI activation along different stages of the central auditory system and across hemispheres for a group of normal hearing listeners. 4-kHz-bandpass filtered noise stimuli were presented monaurally to each ear at levels from 37 to 97dB SPL. One diotic condition and a silence condition were included as control conditions. The participants completed a categorical loudness scaling procedure with similar stimuli before auditory fMRI was performed. The relationship between brain activity, as inferred from blood oxygenation level dependent (BOLD) contrasts, and both sound level and loudness estimates were analyzed by means of functional activation maps and linear mixed effects models for various anatomically defined regions of interest in the ascending auditory pathway and in the cortex. Our findings are overall in line with the notion that fMRI activation in several regions within auditory cortex as well as in certain stages of the ascending auditory pathway might be more a direct linear reflection of perceived loudness rather than of sound pressure level. The results indicate distinct functional differences between midbrain and cortical areas as well as between specific regions within auditory cortex, suggesting a systematic hierarchy in terms of lateralization and the representation of level and loudness.¹.

Spectral and binaural loudness summation for hearing-impaired listeners

Sensorineural hearing loss typically results in a steepened loudness function and a reduced dynamic range from elevated thresholds to uncomfortably loud levels for narrowband and broadband signals. Restoring narrowband loudness perception for hearing-impaired (HI) listeners can lead to overly loud perception of broadband signals and it is unclear how binaural presentation affects loudness perception in this case. Here, loudness perception quantified by categorical loudness scaling for nine normal-hearing (NH) and ten HI listeners was compared for signals with different bandwidth and different spectral shape in monaural and in binaural conditions. For the HI listeners, frequency- and level-dependent amplification was used to match the narrowband monaural loudness functions of the NH listeners. The average loudness functions for NH and HI listeners showed good agreement for monaural broadband signals. However, HI listeners showed substantially greater loudness for binaural broadband signals than NH listeners: on average a 14.1 dB lower level was required to reach "very loud" (range 30.8 to -3.7 dB). Overall, with narrowband loudness compensation, a given binaural loudness for broadband signals above "medium loud" was reached at systematically lower levels for HI than for NH listeners. Such increased binaural loudness summation was not found for loudness categories below "medium loud" or for narrowband signals. Large individual variations in the increased loudness summation were observed and could not be explained by the audiogram or the narrowband loudness functions.

Categorical scaling of partial loudness in a condition of masking release

Categorical loudness scaling was used to measure suprathreshold release from masking. The signal was a 986-Hz sinusoid that was embedded in a bandpass-filtered masking noise. This noise was either unmodulated or was amplitude modulated with a square-wave modulator. The unmodulated noise had either the same level as the modulated noise or had a level that was reduced by the difference in thresholds for the 986-Hz signal obtained with the modulated and unmodulated noise masker presented at the same level (i.e., the masking release). A comparison with loudness matching data of the same set of subjects showed that the data obtained with loudness scaling capture main aspects of the change in suprathreshold perception of the sinusoid when the masker was modulated. The scaling data for the signal masked by the unmodulated noise with the reduced masker level were similar to that for the signal embedded in the modulated noise. This similarity supports the hypothesis that the mechanism eliciting the masking release is effectively reducing the masker level.

Categorical loudness scaling and equal-loudness contours in listeners with normal hearing and hearing loss

This study describes procedures for constructing equal-loudness contours (ELCs) in units of phons from categorical loudness scaling (CLS) data and characterizes the impact of hearing loss on these estimates of loudness. Additionally, this study developed a metric, level-dependent loudness loss, which uses CLS data to specify the deviation from normal loudness perception at various loudness levels and as function of frequency for an individual listener with hearing loss. CLS measurements were made in 87 participants with hearing loss and 61 participants with normal hearing. An assessment of the reliability of CLS measurements was conducted on a subset of the data. CLS measurements were reliable. There was a systematic increase in the slope of the low-level segment of the CLS functions with increase in the degree of hearing loss. ELCs derived from CLS measurements were similar to standardized ELCs (International Organization for Standardization, ISO 226:2003). The presence of hearing loss decreased the vertical spacing of the ELCs, reflecting loudness recruitment and reduced cochlear compression. Representing CLS data in phons may lead to wider acceptance of CLS measurements. Like the audiogram that specifies hearing loss at threshold, level-dependent loudness loss describes deficit for suprathreshold sounds. Such information may have implications for the fitting of hearing aids.