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dc.contributor.authorMandalapu, Hareesh
dc.contributor.authorReddy, P. N. Aravinda
dc.contributor.authorRamachandra, Raghavendra
dc.contributor.authorRao, Krothapalli Sreenivasa
dc.contributor.authorMitra, Pabitra
dc.contributor.authorPrasanna, S. R. Mahadeva
dc.contributor.authorBusch, Christoph
dc.date.accessioned2023-01-11T08:53:03Z
dc.date.available2023-01-11T08:53:03Z
dc.date.created2022-01-13T10:40:55Z
dc.date.issued2021
dc.identifier.citationIEEE Access. 2021, 9 153240-153257.en_US
dc.identifier.issn2169-3536
dc.identifier.urihttps://hdl.handle.net/11250/3042568
dc.description.abstractSmartphones have been employed with biometric-based verification systems to provide security in highly sensitive applications. Audio-visual biometrics are getting popular due to their usability, and also it will be challenging to spoof because of their multimodal nature. In this work, we present an audio-visual smartphone dataset captured in five different recent smartphones. This new dataset contains 103 subjects captured in three different sessions considering the different real-world scenarios. Three different languages are acquired in this dataset to include the problem of language dependency of the speaker recognition systems. These unique characteristics of this dataset will pave the way to implement novel state-of-the-art unimodal or audio-visual speaker recognition systems. We also report the performance of the bench-marked biometric verification systems on our dataset. The robustness of biometric algorithms is evaluated towards multiple dependencies like signal noise, device, language and presentation attacks like replay and synthesized signals with extensive experiments. The obtained results raised many concerns about the generalization properties of state-of-the-art biometrics methods in smartphones.en_US
dc.language.isoengen_US
dc.publisherIEEEen_US
dc.rightsNavngivelse 4.0 Internasjonal*
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/deed.no*
dc.titleMultilingual Audio-Visual Smartphone Dataset and Evaluationen_US
dc.title.alternativeMultilingual Audio-Visual Smartphone Dataset and Evaluationen_US
dc.typePeer revieweden_US
dc.typeJournal articleen_US
dc.description.versionpublishedVersionen_US
dc.source.pagenumber153240-153257en_US
dc.source.volume9en_US
dc.source.journalIEEE Accessen_US
dc.identifier.doi10.1109/ACCESS.2021.3125485
dc.identifier.cristin1980198
cristin.ispublishedtrue
cristin.fulltextoriginal
cristin.qualitycode1


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