Acoustic Transparency in Hearables - Perceptual Sound Quality Evaluations

Schepker, Henning; Denk, Florian; Kollmeier, Birger; Doclo, Simon

doi:10.17743/jaes.2020.0045

Cited by 21 publications

(47 citation statements)

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“…3 with spectral manipulations from a real-world acoustical scenario. Instead of manipulating a linear spectral filter slope of the stimuli between 0.125 and 8 kHz, we used the acoustic transfer functions of a dummy head recorded in an acoustics lab 25 . In one condition, the dummy head had “open ears”, that is, it was not equipped with any hearing device.…”

Section: Resultsmentioning

confidence: 99%

“…Headphones were equalized to obtain a flat magnitude response at the KEMAR eardrum by using regularized inversion as implemeted in the AKtools toolbox 48 . Transfer functions were measured using a GRAS 45BB-12 KEMAR Head & Torso with anthropometric pinnae in an acoustics lab with reverberation time of around 0.45 s with loudspeakers in a frontal direction, see Schepker et al 25 for details. Due to the Covid-19 pandemic, in Exp.…”

Section: Methodsmentioning

confidence: 99%

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Adaptive auditory brightness perception

Siedenburg

Barg

Schepker

2021

Sci Rep

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Perception adapts to the properties of prior stimulation, as illustrated by phenomena such as visual color constancy or speech context effects. In the auditory domain, only little is known about adaptive processes when it comes to the attribute of auditory brightness. Here, we report an experiment that tests whether listeners adapt to spectral colorations imposed on naturalistic music and speech excerpts. Our results indicate consistent contrastive adaptation of auditory brightness judgments on a trial-by-trial basis. The pattern of results suggests that these effects tend to grow with an increase in the duration of the adaptor context but level off after around 8 trials of 2 s duration. A simple model of the response criterion yields a correlation of r = .97 with the measured data and corroborates the notion that brightness perception adapts on timescales that fall in the range of auditory short-term memory. Effects turn out to be similar for spectral filtering based on linear spectral filter slopes and filtering based on a measured transfer function from a commercially available hearing device. Overall, our findings demonstrate the adaptivity of auditory brightness perception under realistic acoustical conditions.

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Section: Resultsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Adaptive auditory brightness perception

Siedenburg

Barg

Schepker

2021

Sci Rep

Self Cite

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“…The algorithm names are provided in Figure 2, and the reader is referred to Schepker et al (2019) Hear-Through Mode. The hear-through mode (HTM) database was taken from the study of Schepker et al (2020). The database consists of 120 speech (female, male) and music (jazz, piano) items, sampled at 48 kHz.…”

Section: Databasesmentioning

confidence: 99%

“…Disregarding the perceptual limits results in a slightly lower Accuracy of 0.92 compared with the Accuracy of 0.93 for the standard GPSM q , which incorporates such perceptual limit by default. For further details about the devices, refer toSchepker et al (2020). GPSM…”

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confidence: 99%

Instrumental Quality Predictions and Analysis of Auditory Cues for Algorithms in Modern Headphone Technology

et al. 2021

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Smart headphones or hearables use different types of algorithms such as noise cancelation, feedback suppression, and sound pressure equalization to eliminate undesired sound sources or to achieve acoustical transparency. Such signal processing strategies might alter the spectral composition or interaural differences of the original sound, which might be perceived by listeners as monaural or binaural distortions and thus degrade audio quality. To evaluate the perceptual impact of these distortions, subjective quality ratings can be used, but these are time consuming and costly. Auditory-inspired instrumental quality measures can be applied with less effort and may also be helpful in identifying whether the distortions impair the auditory representation of monaural or binaural cues. Therefore, the goals of this study were (a) to assess the applicability of various monaural and binaural audio quality models to distortions typically occurring in hearables and (b) to examine the effect of those distortions on the auditory representation of spectral, temporal, and binaural cues. Results showed that the signal processing algorithms considered in this study mainly impaired (monaural) spectral cues. Consequently, monaural audio quality models that capture spectral distortions achieved the best prediction performance. A recent audio quality model that predicts monaural and binaural aspects of quality was revised based on parts of the current data involving binaural audio quality aspects, leading to improved overall performance indicated by a mean Pearson linear correlation of 0.89 between obtained and predicted ratings.

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“…They found significant differences on sound localisation performance which depended on the type of HWD, where active hearing protection devices induced more errors than passive devices. Schepker et al [19] and Denk et al [20] investigated the sound quality of commercially available hear-through devices with subjective listening experiments. In [19], perceptual sound quality was evaluated.…”

Section: Acoustics and Evaluation Of Head-worn Devicesmentioning

confidence: 99%

Auditory model-based estimation of the effect of head-worn devices on frontal horizontal localisation

2022

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Auditory localisation accuracy may be degraded when a head-worn device (HWD), such as a helmet or hearing protector, is used. A computational method is proposed in this study for estimating how horizontal plane localisation is impaired by a HWD through distortions of interaural cues. Head-related impulse responses (HRIRs) of different HWDs were measured with a KEMAR and a binaural auditory model was used to compute interaural cues from HRIR-convolved noise bursts. A shallow neural network (NN) was trained with data from a subjective listening experiment, where horizontal plane localisation was assessed while wearing different HWDs. Interaural cues were used as features to estimate perceived direction and position uncertainty (standard deviation) of a sound source in the horizontal plane with the NN. The NN predicted the position uncertainty of localisation among subjects for a given HWD with an average estimation error of 1°. The obtained results suggest that it is possible to predict the degradation of localisation ability for specific HWDs in the frontal horizontal plane using the method.

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Acoustic Transparency in Hearables - Perceptual Sound Quality Evaluations

Cited by 21 publications

References 0 publications

Adaptive auditory brightness perception

Adaptive auditory brightness perception

Instrumental Quality Predictions and Analysis of Auditory Cues for Algorithms in Modern Headphone Technology

Auditory model-based estimation of the effect of head-worn devices on frontal horizontal localisation

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