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JFA based Speaker Recognition using Delta-Phase and MFCC features

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dc.contributor.author Ahilan, K.
dc.contributor.author Dean, D.
dc.contributor.author Sridharan, S.
dc.date.accessioned 2021-03-15T03:22:02Z
dc.date.accessioned 2022-06-27T10:02:16Z
dc.date.available 2021-03-15T03:22:02Z
dc.date.available 2022-06-27T10:02:16Z
dc.date.issued 2012
dc.identifier.citation Kanagasundaram, A., Dean, D., & Sridharan, S. (2012). JFA based speaker recognition using delta-phase and MFCC features. In Speech Science and Technology 2012: Proceedings of the 14th Australasian International Conference on Speech Science and Technology (pp. 1-4). The Australasian Speech Science and Technology Association (ASSTA). en_US
dc.identifier.uri http://repo.lib.jfn.ac.lk/ujrr/handle/123456789/1848
dc.description.abstract This paper investigates the use of mel-frequency deltaphase (MFDP) features in comparison to, and in fusion with, traditional mel-frequency cepstral coefficient (MFCC) features within joint factor analysis (JFA) speaker verification. MFCC features, commonly used in speaker recognition systems, are derived purely from the magnitude spectrum, with the phase spectrum completely discarded. In this paper, we investigate if features derived from the phase spectrum can provide additional speaker discriminant information to the traditional MFCC approach in a JFA based speaker verification system. Results are presented which provide a comparison of MFCC-only, MFDPonly and score fusion of the two approaches within a JFA speaker verification approach. Based upon the results presented using the NIST 2008 Speaker Recognition Evaluation (SRE) dataset, we believe that, while MFDP features alone cannot compete with MFCC features, MFDP can provide complementary information that result in improved speaker verification performance when both approaches are combined in score fusion, particularly in the case of shorter utterances. en_US
dc.language.iso en en_US
dc.subject speaker verification en_US
dc.subject MFCC features en_US
dc.title JFA based Speaker Recognition using Delta-Phase and MFCC features en_US
dc.type Article en_US


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