A speech-based computational auditory signal processing and perception model

Relaño-Iborra, Helia; Zaar, Johannes; Dau, Torsten

doi:10.1121/1.5129114

Cited by 22 publications

(17 citation statements)

References 55 publications

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“…it is applied to the evaluation of perceptual similarity between piano note recordings (Osses et al, 2019a). The choice of evaluating piano sounds was motivated by: (1) the complex spectro-temporal properties present in piano sounds, (2) the fact that piano sounds have been thoroughly studied in physical acoustics and we recently quantified differences psychoacoustically (Chaigne et al, 2019;Osses et al, 2019a), and (3) the fact that the PEMO model has been primarily applied to study artificial sounds (Dau et al, 1996a,b;Jepsen et al, 2008) and speech (Jørgensen & Dau, 2011;Relaño-Iborra et al, 2019) and less often to other types of sounds, including musical instrument sounds (Huber & Kollmeier, 2006). Although Huber & Kollmeier applied this auditory model to more diverse sets of sounds, their central processor was adapted to provide a quality metric and, therefore, the goal in their study was to assess judgments of sound quality rather than simulating performance.…”

Section: Introductionmentioning

confidence: 99%

Perceptual similarity between piano notes: Simulations with a template-based perception model

Osses

Kohlrausch

2021

The Journal of the Acoustical Society of America

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In this paper the auditory model developed by Dau et al. [J. Acoust. Soc. Am. 102, 2892-2905] was used to simulate the perceptual similarity between complex sounds. For this purpose, a central processor stage was developed and attached as a back-end module to the auditory model. As complex sounds, a set of recordings of one note played on seven different pianos was used, whose similarity has been recently measured by Osses et al. [J. Acoust. Soc. Am. 146, 1024-1035] using a 3-AFC discrimination task in noise. The auditory model has several processing stages that are to a greater or lesser extent inspired by physiological aspects of the human normal-hearing system. A set of configurable parameters in each stage affects directly the sound (internal) representations that are further processed in the developed central processor. Therefore, a comprehensive review of the model parameters is given, indicating the configuration we chose. This includes an in-depth description of the auditory adaptation stage, the adaptation loops. Simulations of the similarity task were compared with (1) existing experimental data, where they had a moderate to high correlation, and with (2) simulations using an alternative but similar background noise to that of the experiments, which were used to obtain further information about how the participants' responses were weighted as a function of frequency.

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Section: Introductionmentioning

confidence: 99%

Perceptual similarity between piano notes: Simulations with a template-based perception model

Osses

Kohlrausch

2021

The Journal of the Acoustical Society of America

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“…1c ). The linear effective models are represented by dau1997 [ 31 ] and osses2021 [ 39 ] and the nonlinear effective models are represented by king2019 [ 37 ] and relanoiborra2019 [ 38 ]. Given that for each model a similar level of approximation has been generally used in the design of subsequent model stages, we use the defined categories to reflect the nature of the entire model.…”

Section: Modelsmentioning

confidence: 99%

“…The model relanoiborra2019 can predict speech intelligibility [ 38 ] when coupled with a decision back-end stage [ 38 , 107 ]. Relying on the prediction power of earlier model implementations [ 77 , 108 ], relanoiborra2019 should be able to (1) account for elevated thresholds based on OHC and IHC impairment [ 108 ], and (2) to predict a number of psychoacoustic tasks including simultaneous and forward masking and amplitude modulation [ 77 ].…”

Section: Models In Perspectivementioning

confidence: 99%

A comparative study of eight human auditory models of monaural processing

et al. 2022

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A number of auditory models have been developed using diverging approaches, either physiological or perceptual, but they share comparable stages of signal processing, as they are inspired by the same constitutive parts of the auditory system. We compare eight monaural models that are openly accessible in the Auditory Modelling Toolbox. We discuss the considerations required to make the model outputs comparable to each other, as well as the results for the following model processing stages or their equivalents: Outer and middle ear, cochlear filter bank, inner hair cell, auditory nerve synapse, cochlear nucleus, and inferior colliculus. The discussion includes a list of recommendations for future applications of auditory models.

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“…Virtual acoustic environments have demonstrated versatility in various research areas, as they allow easy manipulations of experimental test conditions or simulated acoustic scenes. Although the evolution of auditory and cognitive models is constantly pursued (Søndergaard and Majdak 2013;Relaño-Iborra et al, 2019), listening experiments are still considered to be the gold standard (Brinkmann et al, 2019, Pausch andFels 2019), usually necessitating a defined 3D environment. For easy manipulation of experimental conditions, it is desirable that acoustic conditions, types, positions, and the orientations of the involved sound sources, as well as the order of examined conditions, can be changed without physical modifications of the laboratory.…”

Section: Introductionmentioning

confidence: 99%

Multi-Detailed 3D Architectural Framework for Sound Perception Research in Virtual Reality

Llorca-Bofí

Vorländer

2021

Front. Built Environ.

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The presentation of architectural design in simulation environments demands strong 3D modeling abilities. Architects usually demonstrate presentation skills that mostly address researchers in the building simulation field. However, there is still a gap between the architect’s deliverable and the contextual scenario for overarching research purposes, mainly caused by the lack of knowledge in the areas where research disciplines overlap. This dilemma is particularly present in the practice of 3D modeling for sound perception research in virtual reality since the building modelers must also gather diverse pieces of knowledge into a contained scenario: ranging from sound sources, sound propagation models to physically based material models. Grounded on this need, this article presents a comprehensive framework, defined by the visual and acoustic cues—geometries, materials, sources, receivers, and postprocessing—on one side and three levels of detail on the other. In this way, very specific research application needs can be covered, as well as a modular concept for future modeling demands. The interconnection between every model element is particularly designed, enabling the assembly among different modalities at different levels of detail. Finally, it provides targeted modeling strategies for architects, depicted in one indoor and one outdoor demonstration for auditory-visual research.

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A speech-based computational auditory signal processing and perception model

Cited by 22 publications

References 55 publications

Perceptual similarity between piano notes: Simulations with a template-based perception model

Perceptual similarity between piano notes: Simulations with a template-based perception model

A comparative study of eight human auditory models of monaural processing

Multi-Detailed 3D Architectural Framework for Sound Perception Research in Virtual Reality

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