A Novel Voice Activity Detection for Multi-Channel Noise Reduction

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dc.authorid0000-0003-3017-7651
dc.contributor.authorÇolak, Ramazan
dc.contributor.authorAkdeniz, Rafet
dc.date.accessioned2022-05-11T14:03:05Z
dc.date.available2022-05-11T14:03:05Z
dc.date.issued2021
dc.departmentFakülteler, Çorlu Mühendislik Fakültesi, Elektronik ve Haberleşme Mühendisliği Bölümü
dc.description.abstractIn this study, a voice activity detection technique is designed using features such as short-term energy, periodicity and spectral flatness. The desired results are obtained by using these three features, even at low signal to noise ratio values. In addition, performance of multi-channel noise reduction algorithms such as Wiener speech distortion weighted, spatial prediction, minimum variance distortion-less response are compared using the proposed voice activity detection. Two different audio signals and three different noise types are used in the experiment. Noisy speech and only detection of noisy areas have been performed by proposed voice activity detection algorithm. The filter coefficients have been calculated for each filter algorithm used after detection of noisy speech and only noisy areas. The calculated filter coefficients have been multiplied by the frequency components of the signal received from the reference microphone to obtain an enhanced signal. Segmental signal to noise ratio, an objective method, and mean opinion score as a subjective method have been used to evaluate the performance of the filters. Speech distortion weighted Wiener filter has been found to be the best filter for noise reduction performance.
dc.description.sponsorship[NKUBAP.06]; [YL.18.156]
dc.description.sponsorshipThis work was supported by the Tekirda Namk Kemal University Scienti~c Research Project Commission under Grant NKUBAP.06.YL.18.156.
dc.identifier.doi10.1109/ACCESS.2021.3086364
dc.identifier.endpage91026
dc.identifier.issn2169-3536
dc.identifier.scopus2-s2.0-85107337715
dc.identifier.scopusqualityQ1
dc.identifier.startpage91017
dc.identifier.urihttps://doi.org/10.1109/ACCESS.2021.3086364
dc.identifier.urihttps://hdl.handle.net/20.500.11776/4598
dc.identifier.volume9
dc.identifier.wosWOS:000673647200001
dc.identifier.wosqualityQ2
dc.indekslendigikaynakWeb of Science
dc.indekslendigikaynakScopus
dc.institutionauthorAkdeniz, Rafet
dc.language.isoen
dc.publisherIeee-Inst Electrical Electronics Engineers Inc
dc.relation.ispartofIeee Access
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/openAccess
dc.subjectAdaptive filter
dc.subjectnoise reduction
dc.subjectspeech enhancement
dc.subjectvoice activity detection
dc.subjectSpeech Enhancement
dc.titleA Novel Voice Activity Detection for Multi-Channel Noise Reduction
dc.typeArticle

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