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SR-SRP: Super-Resolution based SRP-PHAT for Sound Source Localization and Tracking

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dc.contributor.authorCho, Jae-Heung-
dc.contributor.authorChang, Joon-Hyuk-
dc.date.accessioned2024-11-28T08:36:23Z-
dc.date.available2024-11-28T08:36:23Z-
dc.date.issued2023-08-
dc.identifier.issn1990-9772-
dc.identifier.urihttps://scholarworks.bwise.kr/hanyang/handle/2021.sw.hanyang/195427-
dc.description.abstractSound source localization and tracking have been extensively studied. Recently, there has been considerable interest in highly reverberant scenarios and steered response power with phase transform (SRP-PHAT) based models have shown a good performance. However, these models still have limitations because the SRP-PHAT algorithm cannot represent the direction of the source in such adverse environments. In this paper, we propose a novel structure combining a super-resolution model and a single sound source localization model that allows to improve direction estimation performance. The proposed method generates a robust power map that accurately represents the direction of the source, even in poor scenarios. Furthermore, the proposed structure has a lower computational cost because it uses a low-resolution map. Experimental results on simulation-based and real-world data show that the proposed method outperforms the state-of-the-art model, Cross3D.-
dc.format.extent5-
dc.language영어-
dc.language.isoENG-
dc.titleSR-SRP: Super-Resolution based SRP-PHAT for Sound Source Localization and Tracking-
dc.typeArticle-
dc.identifier.doi10.21437/Interspeech.2023-2369-
dc.identifier.scopusid2-s2.0-85171580115-
dc.identifier.wosid001186650303190-
dc.identifier.bibliographicCitationProceedings of the Annual Conference of the International Speech Communication Association, INTERSPEECH, v.2023-August, pp 3769 - 3773-
dc.citation.titleProceedings of the Annual Conference of the International Speech Communication Association, INTERSPEECH-
dc.citation.volume2023-August-
dc.citation.startPage3769-
dc.citation.endPage3773-
dc.type.docTypeProceedings Paper-
dc.description.isOpenAccessN-
dc.description.journalRegisteredClassscopus-
dc.relation.journalResearchAreaAcoustics-
dc.relation.journalResearchAreaAudiology & Speech-Language Pathology-
dc.relation.journalResearchAreaComputer Science-
dc.relation.journalWebOfScienceCategoryAcoustics-
dc.relation.journalWebOfScienceCategoryAudiology & Speech-Language Pathology-
dc.relation.journalWebOfScienceCategoryComputer Science, Artificial Intelligence-
dc.relation.journalWebOfScienceCategoryComputer Science, Software Engineering-
dc.subject.keywordPlusOptical resolving power-
dc.subject.keywordPlusImage super resolutions-
dc.subject.keywordPlusLocalization and tracking-
dc.subject.keywordPlusPerformance-
dc.subject.keywordPlusPhase transform-
dc.subject.keywordPlusResponse power-
dc.subject.keywordPlusSound source localization-
dc.subject.keywordPlusSound source tracking-
dc.subject.keywordPlusSteered response power with phase transform-
dc.subject.keywordPlusSuperresolution-
dc.subject.keywordPlusTransform algorithm-
dc.subject.keywordPlusSpeech communication-
dc.subject.keywordAuthorimage super-resolution-
dc.subject.keywordAuthorsound source localization and tracking-
dc.subject.keywordAuthorSRP-PHAT-
dc.identifier.urlhttps://www.isca-speech.org/archive/interspeech_2023/cho23_interspeech.html-
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