Prediction and Controlling of Auditory Perception in Augmented Environments. A Loudness-Based Dynamic Mixing Technique

At the core of augmented reality audio (ARA) technology lies the ARA mix, a process responsible for the assignment of a virtual environment to a real one. Legacy ARA mix models have focused on the natural reproduction of the real environment, whereas the virtual environment is simply mixed through f...

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Autores principales:	Nikolaos Moustakas, Andreas Floros, Emmanouel Rovithis, Konstantinos Vogklis
Formato:	article
Lenguaje:	EN
Publicado:	MDPI AG 2021
Materias:	augmented reality audio binaural loudness dynamic mix adaptive environments Technology T Engineering (General). Civil engineering (General) TA1-2040 Biology (General) QH301-705.5 Physics QC1-999 Chemistry QD1-999
Acceso en línea:	https://doaj.org/article/64936c4af5fa4eae9ee5390571d5a803
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id	oai:doaj.org-article:64936c4af5fa4eae9ee5390571d5a803
record_format	dspace
spelling	oai:doaj.org-article:64936c4af5fa4eae9ee5390571d5a8032021-11-25T16:41:39ZPrediction and Controlling of Auditory Perception in Augmented Environments. A Loudness-Based Dynamic Mixing Technique10.3390/app1122109442076-3417https://doaj.org/article/64936c4af5fa4eae9ee5390571d5a8032021-11-01T00:00:00Zhttps://www.mdpi.com/2076-3417/11/22/10944https://doaj.org/toc/2076-3417At the core of augmented reality audio (ARA) technology lies the ARA mix, a process responsible for the assignment of a virtual environment to a real one. Legacy ARA mix models have focused on the natural reproduction of the real environment, whereas the virtual environment is simply mixed through fixed gain methods. This study presents a novel approach of a dynamic ARA mix that facilitates a smooth adaptation of the virtual environment to the real one, as well as dynamic control of the virtual audio engine, by taking into account the inherent characteristics of both ARA technology and binaural auditory perception. A prototype feature extraction technique of auditory perception characteristics through a real-time binaural loudness prediction method was used to upgrade the legacy ARA mix model into a dynamic model, which was evaluated through benchmarks and subjective tests and showed encouraging results in terms of functionality and acceptance.Nikolaos MoustakasAndreas FlorosEmmanouel RovithisKonstantinos VogklisMDPI AGarticleaugmented reality audiobinaural loudnessdynamic mixadaptive environmentsTechnologyTEngineering (General). Civil engineering (General)TA1-2040Biology (General)QH301-705.5PhysicsQC1-999ChemistryQD1-999ENApplied Sciences, Vol 11, Iss 10944, p 10944 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	augmented reality audio binaural loudness dynamic mix adaptive environments Technology T Engineering (General). Civil engineering (General) TA1-2040 Biology (General) QH301-705.5 Physics QC1-999 Chemistry QD1-999
spellingShingle	augmented reality audio binaural loudness dynamic mix adaptive environments Technology T Engineering (General). Civil engineering (General) TA1-2040 Biology (General) QH301-705.5 Physics QC1-999 Chemistry QD1-999 Nikolaos Moustakas Andreas Floros Emmanouel Rovithis Konstantinos Vogklis Prediction and Controlling of Auditory Perception in Augmented Environments. A Loudness-Based Dynamic Mixing Technique
description	At the core of augmented reality audio (ARA) technology lies the ARA mix, a process responsible for the assignment of a virtual environment to a real one. Legacy ARA mix models have focused on the natural reproduction of the real environment, whereas the virtual environment is simply mixed through fixed gain methods. This study presents a novel approach of a dynamic ARA mix that facilitates a smooth adaptation of the virtual environment to the real one, as well as dynamic control of the virtual audio engine, by taking into account the inherent characteristics of both ARA technology and binaural auditory perception. A prototype feature extraction technique of auditory perception characteristics through a real-time binaural loudness prediction method was used to upgrade the legacy ARA mix model into a dynamic model, which was evaluated through benchmarks and subjective tests and showed encouraging results in terms of functionality and acceptance.
format	article
author	Nikolaos Moustakas Andreas Floros Emmanouel Rovithis Konstantinos Vogklis
author_facet	Nikolaos Moustakas Andreas Floros Emmanouel Rovithis Konstantinos Vogklis
author_sort	Nikolaos Moustakas
title	Prediction and Controlling of Auditory Perception in Augmented Environments. A Loudness-Based Dynamic Mixing Technique
title_short	Prediction and Controlling of Auditory Perception in Augmented Environments. A Loudness-Based Dynamic Mixing Technique
title_full	Prediction and Controlling of Auditory Perception in Augmented Environments. A Loudness-Based Dynamic Mixing Technique
title_fullStr	Prediction and Controlling of Auditory Perception in Augmented Environments. A Loudness-Based Dynamic Mixing Technique
title_full_unstemmed	Prediction and Controlling of Auditory Perception in Augmented Environments. A Loudness-Based Dynamic Mixing Technique
title_sort	prediction and controlling of auditory perception in augmented environments. a loudness-based dynamic mixing technique
publisher	MDPI AG
publishDate	2021
url	https://doaj.org/article/64936c4af5fa4eae9ee5390571d5a803
work_keys_str_mv	AT nikolaosmoustakas predictionandcontrollingofauditoryperceptioninaugmentedenvironmentsaloudnessbaseddynamicmixingtechnique AT andreasfloros predictionandcontrollingofauditoryperceptioninaugmentedenvironmentsaloudnessbaseddynamicmixingtechnique AT emmanouelrovithis predictionandcontrollingofauditoryperceptioninaugmentedenvironmentsaloudnessbaseddynamicmixingtechnique AT konstantinosvogklis predictionandcontrollingofauditoryperceptioninaugmentedenvironmentsaloudnessbaseddynamicmixingtechnique
_version_	1718413021957586944

Prediction and Controlling of Auditory Perception in Augmented Environments. A Loudness-Based Dynamic Mixing Technique

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