Physiological motivated transmission-lines as front end for loudness models

Pieper, Iko; Mauermann, Manfred; Kollmeier, Birger; Ewert, Stephan D.

doi:10.1121/1.4949540

Cited by 11 publications

(5 citation statements)

References 49 publications

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“…The resulting filter bank did not have a realistic phase response ( Kohlrausch, 1988 ; Oxenham & Dau, 2001 ), and the filters did not vary with level in the way that the auditory filters do ( Moore & Glasberg, 1987 ). Transmission-line models of the cochlea have been used as the basis for loudness models by Pieper, Mauermann, Kollmeier, and Ewert (2016) , but their models required somewhat arbitrary correction filters to give accurate predictions of equal-loudness contours. A model using filters with more realistic level- and frequency-dependent gains and phase responses may be required to account for the effects of component phase on the loudness of complex sounds ( Gockel, Moore, & Patterson, 2002 ).…”

Section: Unresolved Issues and Limitationsmentioning

confidence: 99%

A Loudness Model for Time-Varying Sounds Incorporating Binaural Inhibition

et al. 2016

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This article describes a model of loudness for time-varying sounds that incorporates the concept of binaural inhibition, namely, that the signal applied to one ear can reduce the internal response to a signal at the other ear. For each ear, the model includes the following: a filter to allow for the effects of transfer of sound through the outer and middle ear; a short-term spectral analysis with greater frequency resolution at low than at high frequencies; calculation of an excitation pattern, representing the magnitudes of the outputs of the auditory filters as a function of center frequency; application of a compressive nonlinearity to the output of each auditory filter; and smoothing over time of the resulting instantaneous specific loudness pattern using an averaging process resembling an automatic gain control. The resulting short-term specific loudness patterns are used to calculate broadly tuned binaural inhibition functions, the amount of inhibition depending on the relative short-term specific loudness at the two ears. The inhibited specific loudness patterns are summed across frequency to give an estimate of the short-term loudness for each ear. The overall short-term loudness is calculated as the sum of the short-term loudness values for the two ears. The long-term loudness for each ear is calculated by smoothing the short-term loudness for that ear, again by a process resembling automatic gain control, and the overall loudness impression is obtained by summing the long-term loudness across ears. The predictions of the model are more accurate than those of an earlier model that did not incorporate binaural inhibition.

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Section: Unresolved Issues and Limitationsmentioning

confidence: 99%

A Loudness Model for Time-Varying Sounds Incorporating Binaural Inhibition

et al. 2016

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“…The correction filter, attenuating low and amplifying high frequencies (see Pieper et al, 2016Pieper et al, , 2018 for details), is applied to obtain a frequency-dependent absolute threshold according to ISO 389-7 (2005).…”

Section: Model Extensions and Modificationsmentioning

confidence: 99%

“…To obtain loudness in sones S m (at time step m), a power law with the exponent B is applied to the internal binaural loudness I m and the result scaled with the factor A (Pieper et al, 2016(Pieper et al, , 2018:…”

Section: Data Availability Statementmentioning

confidence: 99%

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

et al. 2021

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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.

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“…The loudness model built by Piper et al based on physiological models provides an idea to solve this problem [15]. However, the physiological model he used did not consider the real middle ear structure.…”

Section: Introductionmentioning

confidence: 99%

A Sound Quality Evaluation Method for Vehicle Interior Noise Based on Auditory Loudness Model

He,

Guo,

Liu

et al. 2024

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When designing and optimizing the hull of vehicles, their sound quality needs to be considered, which greatly depends on the psychoacoustic parameters. However, the traditional psychoacoustic calculation method does not consider the influence of the real human ear anatomic structure, even the loudness which is most related to the auditory periphery. In order to introduce the real physiological structure of the human ear into the evaluation of vehicle sound quality, this paper first carried out the vehicle internal noise test to obtain the experimental samples. Then, the physiological loudness was predicted based on an established human ear physiological model, and the noise evaluation vector was constructed by combining the remaining four psychoacoustic parameters. Finally, the evaluation vector was fitted into the subjective evaluation results of vehicle interior noise by a deep neural network. The results show that our proposed method can estimate the human subjective perception of vehicle interior noise well.

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Physiological motivated transmission-lines as front end for loudness models

Cited by 11 publications

References 49 publications

A Loudness Model for Time-Varying Sounds Incorporating Binaural Inhibition

A Loudness Model for Time-Varying Sounds Incorporating Binaural Inhibition

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

A Sound Quality Evaluation Method for Vehicle Interior Noise Based on Auditory Loudness Model

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