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MIR-GAN : Refining Frame-Level Modality-Invariant Representations with Adversarial Network for Audio-Visual Speech Recognition

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dc.contributor.authorHu, Yuchen
dc.contributor.authorChen, Chen
dc.contributor.authorLi, Ruizhe
dc.contributor.authorZou, Heqing
dc.contributor.authorChng, Eng Siong
dc.contributor.institutionUniversity of Aberdeen.Computing Scienceen
dc.contributor.institutionUniversity of Aberdeen.Computational Linguistics at Aberdeenen
dc.date.accessioned2023-07-11T11:02:01Z
dc.date.available2023-07-11T11:02:01Z
dc.date.issued2023-07-01
dc.format.extent16
dc.format.extent2449074
dc.format.extent2350664
dc.identifier263537369
dc.identifier99a4109b-5551-4506-81c1-5286c669a53b
dc.identifier85174415869
dc.identifier.citationHu, Y, Chen, C, Li, R, Zou, H & Chng, E S 2023, MIR-GAN : Refining Frame-Level Modality-Invariant Representations with Adversarial Network for Audio-Visual Speech Recognition. in Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)., 2023.acl-long.649, Association for Computational Linguistics, Toronto, Canada, pp. 11610-11625, The 61st Annual Meeting of the Association for Computational Linguistics, Toronto, Canada, 9/07/23. < http://arxiv.org/abs/2306.10567v1 >en
dc.identifier.citationconferenceen
dc.identifier.isbn978-1-959429-72-2
dc.identifier.otherBibtex: hu-etal-2023-mir
dc.identifier.otherORCID: /0000-0003-2512-845X/work/138534413
dc.identifier.otherArXiv: http://arxiv.org/abs/2306.10567v1
dc.identifier.urihttps://hdl.handle.net/2164/21187
dc.identifier.urlhttp://arxiv.org/abs/2306.10567v1en
dc.identifier.urlhttps://aclanthology.org/2023.acl-long.649en
dc.language.isoeng
dc.publisherAssociation for Computational Linguistics
dc.relation.ispartofProceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)en
dc.subjectQA75 Electronic computers. Computer scienceen
dc.subject.lccQA75en
dc.titleMIR-GAN : Refining Frame-Level Modality-Invariant Representations with Adversarial Network for Audio-Visual Speech Recognitionen
dc.typeConference itemen

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