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dc.contributor.authorKim, Changil
dc.contributor.authorShin, Hijung Valentina
dc.contributor.authorOh, Tae-Hyun
dc.contributor.authorKaspar, Alexandre
dc.contributor.authorElgharib, Mohamed
dc.contributor.authorMatusik, Wojciech
dc.date.accessioned2020-04-22T02:40:21Z
dc.date.available2020-04-22T02:40:21Z
dc.date.issued2018-12
dc.identifier.isbn978-3-030-20873-8
dc.identifier.isbn978-3-030-20872-1
dc.identifier.issn1611-3349
dc.identifier.issn0302-9743
dc.identifier.urihttps://hdl.handle.net/1721.1/124778
dc.description.abstractIn this paper, we study the associations between human faces and voices. Audiovisual integration, specifically the integration of facial and vocal information is a well-researched area in neuroscience. It is shown that the overlapping information between the two modalities plays a significant role in perceptual tasks such as speaker identification. Through an online study on a new dataset we created, we confirm previous findings that people can associate unseen faces with corresponding voices and vice versa with greater than chance accuracy. We computationally model the overlapping information between faces and voices and show that the learned cross-modal representation contains enough information to identify matching faces and voices with performance similar to that of humans. Our representation exhibits correlations to certain demographic attributes and features obtained from either visual or aural modality alone. We release our dataset of audiovisual recordings and demographic annotations of people reading out short text used in our studies. ©2019 keywords: face-voice association; multi-modal representation learningen_US
dc.language.isoen
dc.publisherSpringer Natureen_US
dc.relation.isversionof10.1007/978-3-030-20873-8_18en_US
dc.rightsCreative Commons Attribution-Noncommercial-Share Alikeen_US
dc.rights.urihttp://creativecommons.org/licenses/by-nc-sa/4.0/en_US
dc.sourcearXiven_US
dc.titleOn learning associations of faces and voicesen_US
dc.typeArticleen_US
dc.identifier.citationKim, Changil, et al., "On learning associations of faces and voices." In Jawahar, C., H. Li, G.Mori, and K. Schindler, eds., Computer vision: 14th Asian Conference on Computer Vision (ACCV 2018), December 2–6, 2018, Perth, Western Australia. Lecture notes in computer science 11365 (Cham: Springer Nature, 2018): p. 276-92 doi 10.1007/978-3-030-20873-8_18 ©2018 Author(s)en_US
dc.contributor.departmentMassachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratoryen_US
dc.relation.journalLecture notes in computer scienceen_US
dc.eprint.versionOriginal manuscripten_US
dc.type.urihttp://purl.org/eprint/type/ConferencePaperen_US
eprint.statushttp://purl.org/eprint/status/NonPeerRevieweden_US
dc.date.updated2019-06-21T16:35:07Z
dspace.date.submission2019-06-21T16:35:14Z
mit.journal.volume11365en_US


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