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Residual Lsf Vector Quantization Using Arma Prediction

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dc.contributor.author Özaydın, Selma
dc.date.accessioned 2023-12-12T10:04:33Z
dc.date.available 2023-12-12T10:04:33Z
dc.date.issued 2016
dc.identifier.citation Özaydın, Selma (2016). "Residual Lsf Vector Quantization Using Arma Prediction", International Journal of Applied Mathematics, Electronics and Computers, Vol. 4, pp. 79-81. tr_TR
dc.identifier.issn 2147-8228
dc.identifier.uri http://hdl.handle.net/20.500.12416/6772
dc.description.abstract The residual LSF vector quantization yields bit rate reduction in the vocoders. In this work, a residual LSF vector quantization obtained from Auto Regressive Moving Average (ARMA) prediction is proposed for designing codebooks at very low bit rates. This residual quantization method is applied to multi stage vector quantization method and codebooks are designed. For each codebook, the effectiveness and quality are investigated by calculating the spectral distortion and outliers. The proposed quantization method reduced the distortion without any additional complexity. tr_TR
dc.language.iso eng tr_TR
dc.rights info:eu-repo/semantics/openAccess tr_TR
dc.subject Very Low Bit Rate tr_TR
dc.subject Speech Processing tr_TR
dc.subject Residual Vector Quantization tr_TR
dc.subject Formant Tracking tr_TR
dc.subject ARMA Prediction tr_TR
dc.title Residual Lsf Vector Quantization Using Arma Prediction tr_TR
dc.type article tr_TR
dc.relation.journal International Journal of Applied Mathematics, Electronics and Computers tr_TR
dc.contributor.authorID 253019 tr_TR
dc.identifier.volume 4 tr_TR
dc.identifier.startpage 79 tr_TR
dc.identifier.endpage 81 tr_TR
dc.contributor.department Çankaya Üniversitesi, Mühendislik Fakültesi, Bilgisayar Mühendisliği Bölümü tr_TR


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