The SONICOM Project: Artificial Intelligence-Driven Immersive Audio, From Personalization to Modeling

dc.centroE.T.S.I. Telecomunicaciónes_ES
dc.contributor.authorPicinali, Lorenzo
dc.contributor.authorKatz, Brian FG
dc.contributor.authorGeronazzo, Michele
dc.contributor.authorMajdak, Piotr
dc.contributor.authorReyes-Lecuona, Arcadio
dc.contributor.authorVinciarelli, Alessandro
dc.date.accessioned2025-11-05T13:23:11Z
dc.date.available2025-11-05T13:23:11Z
dc.date.issued2022-10-27
dc.departamentoTecnología Electrónicaes_ES
dc.description.abstractEvery individual perceives spatial audio differently, due in large part to the unique and complex shape of ears and head. Therefore, high-quality, headphone-based spatial audio should be uniquely tailored to each listener in an effective and efficient manner. Artificial intelligence (AI) is a powerful tool that can be used to drive forward research in spatial audio personalization. The SONICOM project aims to employ a data-driven approach that links physiological characteristics of the ear to the individual acoustic filters, which allows us to localize sound sources and perceive them as being located around us. A small amount of data acquired from users could allow personalized audio experiences, and AI could facilitate this by offering a new perspective on the matter. A Bayesian approach to computational neuroscience and binaural sound reproduction will be linked to create a metric for AI-based algorithms that will predict realistic spatial audio quality. Being able to consistently and repeatedly evaluate and quantify the improvements brought by technological advancements, as well as the impact these have on complex interactions in virtual environments, will be key for the development of new techniques and for unlocking new approaches to understanding the mechanisms of human spatial hearing and communication.es_ES
dc.description.sponsorshipEuropean Union’s Horizon 2020 Research and Innovation Programes_ES
dc.identifier.citationL. Picinali, B. F. Katz, M. Geronazzo, P. Majdak, A. Reyes-Lecuona and A. Vinciarelli, "The SONICOM Project: Artificial Intelligence-Driven Immersive Audio, From Personalization to Modeling [Applications Corner]," in IEEE Signal Processing Magazine, vol. 39, no. 6, pp. 85-88, Nov. 2022, doi: 10.1109/MSP.2022.3182929. keywords: {Spatial audio;Virtual environments;Physiology;Standardization;Predictive models;Data models;Artificial intelligence;Computational neuroscience;Bayes methods},es_ES
dc.identifier.doi10.1109/MSP.2022.3182929
dc.identifier.issn1053-5888
dc.identifier.urihttps://hdl.handle.net/10630/40615
dc.language.isoenges_ES
dc.publisherIEEEes_ES
dc.relation.projectIDinfo:eu-repo/grantAgreement/EC/H2020/101017743)es_ES
dc.rights.accessRightsopen accesses_ES
dc.subjectNeurociencia computacionales_ES
dc.subjectInteligencia artificiales_ES
dc.subjectFisiologíaes_ES
dc.subjectBioinformáticaes_ES
dc.subject.otherSpatial audioes_ES
dc.subject.otherVirtual environmentses_ES
dc.subject.otherPhysiologyes_ES
dc.subject.otherStandardizationes_ES
dc.subject.otherPredictive modelses_ES
dc.subject.otherData modelses_ES
dc.subject.otherArtificial intelligencees_ES
dc.subject.otherBayes methodses_ES
dc.subject.otherComputational neurosciencees_ES
dc.titleThe SONICOM Project: Artificial Intelligence-Driven Immersive Audio, From Personalization to Modelinges_ES
dc.typejournal articlees_ES
dc.type.hasVersionAMes_ES
dspace.entity.typePublication
relation.isAuthorOfPublication05db8acb-40ab-48ba-be98-3eb847047e46
relation.isAuthorOfPublication.latestForDiscovery05db8acb-40ab-48ba-be98-3eb847047e46

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