Speaker change detection for conversational speech using synthesized voice embedding

dc.contributor.authorKrishnathasan, M
dc.contributor.authorAmalraj, CRJ
dc.contributor.editorSudantha, BH
dc.date.accessioned2022-11-18T06:38:04Z
dc.date.available2022-11-18T06:38:04Z
dc.date.issued2019-12
dc.description.abstractSpeaker change detection is a prominent area of research in voice tasks for many years but used in very limited areas. Speech segmentation, feature extraction, and classification techniques are used as pipeline modules to detect speaker change in speech signals like conversations. This paper provides an approach to detect speaker changes in a conversational speech. Along with that, this paper demonstrates experiments on various sub modules and hyper parameters in the proposed pipeline.en_US
dc.identifier.citationM. Krishnathasan and C. R. J. Amalraj, "Speaker Change Detection for Conversational Speech using Synthesized Voice Embedding," 2019 4th International Conference on Information Technology Research (ICITR), 2019, pp. 1-5, doi: 10.1109/ICITR49409.2019.9407791.en_US
dc.identifier.conference4th International Conference in Information Technology Research 2019en_US
dc.identifier.departmentInformation Technology Research Unit, Faculty of Information Technology, University of Moratuwa.en_US
dc.identifier.doidoi: 10.1109/ICITR49409.2019.9407791en_US
dc.identifier.facultyITen_US
dc.identifier.placeColombo,Sri Lankaen_US
dc.identifier.proceedingProceedings of the 4th International Conference in Information Technology Research 2019en_US
dc.identifier.urihttp://dl.lib.uom.lk/handle/123/19564
dc.identifier.year2019en_US
dc.language.isoenen_US
dc.publisherInformation Technology Research Unit, Faculty of Information Technology, University of Moratuwa, Sri Lankaen_US
dc.relation.urihttps://ieeexplore.ieee.org/document/9407791/en_US
dc.subjectSpeaker Change Detectionen_US
dc.subjectVoice Clusteringen_US
dc.subjectMachine learningen_US
dc.titleSpeaker change detection for conversational speech using synthesized voice embeddingen_US
dc.typeConference-Full-texten_US

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