2013 Cilt 18 Sayı 1

Permanent URI for this collectionhttps://hdl.handle.net/11452/11683

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Browsing by BUU Author "Hanilçi, Cemal"

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    Effects of background data duration on speaker verification performance
    (Uludağ Üniversitesi, 2012-12-21) Hanilçi, Cemal; Ertaş, Figen; Mühendislik Mimarlık Fakültesi; Elektronik Mühendisliği Bölümü
    Gaussian mixture models with universal background model (GMM-UBM) and vector quantization with universal background model (VQ-UBM) are the two well-known classifiers used for speaker verification. Generally, UBM is trained with many hours of speech from a large pool of different speakers. In this study, we analyze the effect of data duration used to train UBM on text-independent speaker verification performance using GMM-UBM and VQ-UBM modeling techniques. Experiments carried out NIST 2002 speaker recognition evaluation (SRE) corpus show that background data duration to train UBM has small impact on recognition performance for GMM-UBM and VQ-UBM classifiers.