About: Score Fusion in Text-Dependent Speaker Recognition Systems     Goto   Sponge   NotDistinct   Permalink

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  • According to some significant advantages, the text-dependent speaker recognition is still widely used in biometric systems. These systems are, in comparison with the text-independent, more accurate and resistant against the replay attacks. There are many approaches regarding the text-dependent recognition. This paper introduces a combination of classifiers based on fractional distances, biometric dispersion matcher and dynamic time warping. The first two mentioned classifiers are based on a voice imprint. They have low memory requirements while the recognition procedure is fast. This is advantageous especially in low-cost biometric systems supplied by batteries. It is shown that using the trained score fusion, it is possible to reach successful detection rate equal to 98.98 % and 92.19 % in case of microphone mismatch. During verification, system reached equal error rate 2.55 % and 6.77 % when assuming the microphone mismatch. System was tested using Catalan database which consists of 48 speakers (thr
  • According to some significant advantages, the text-dependent speaker recognition is still widely used in biometric systems. These systems are, in comparison with the text-independent, more accurate and resistant against the replay attacks. There are many approaches regarding the text-dependent recognition. This paper introduces a combination of classifiers based on fractional distances, biometric dispersion matcher and dynamic time warping. The first two mentioned classifiers are based on a voice imprint. They have low memory requirements while the recognition procedure is fast. This is advantageous especially in low-cost biometric systems supplied by batteries. It is shown that using the trained score fusion, it is possible to reach successful detection rate equal to 98.98 % and 92.19 % in case of microphone mismatch. During verification, system reached equal error rate 2.55 % and 6.77 % when assuming the microphone mismatch. System was tested using Catalan database which consists of 48 speakers (thr (en)
Title
  • Score Fusion in Text-Dependent Speaker Recognition Systems
  • Score Fusion in Text-Dependent Speaker Recognition Systems (en)
skos:prefLabel
  • Score Fusion in Text-Dependent Speaker Recognition Systems
  • Score Fusion in Text-Dependent Speaker Recognition Systems (en)
skos:notation
  • RIV/00216305:26220/11:PU95036!RIV12-MV0-26220___
http://linked.open...avai/predkladatel
http://linked.open...avai/riv/aktivita
http://linked.open...avai/riv/aktivity
  • P(ED2.1.00/03.0072), P(ME10123), P(VG20102014033), S, Z(MSM0021630513)
http://linked.open...iv/cisloPeriodika
  • 12
http://linked.open...vai/riv/dodaniDat
http://linked.open...aciTvurceVysledku
http://linked.open.../riv/druhVysledku
http://linked.open...iv/duvernostUdaju
http://linked.open...titaPredkladatele
http://linked.open...dnocenehoVysledku
  • 228329
http://linked.open...ai/riv/idVysledku
  • RIV/00216305:26220/11:PU95036
http://linked.open...riv/jazykVysledku
http://linked.open.../riv/klicovaSlova
  • text-dependent speaker recognition, voice imprint, fractional distances, biometric dispersion matcher, dynamic time warping (en)
http://linked.open.../riv/klicoveSlovo
http://linked.open...odStatuVydavatele
  • DE - Spolková republika Německo
http://linked.open...ontrolniKodProRIV
  • [5FE3C6588A5A]
http://linked.open...i/riv/nazevZdroje
  • Lecture Notes in Computer Science (IF 0,513)
http://linked.open...in/vavai/riv/obor
http://linked.open...ichTvurcuVysledku
http://linked.open...cetTvurcuVysledku
http://linked.open...vavai/riv/projekt
http://linked.open...UplatneniVysledku
http://linked.open...v/svazekPeriodika
  • 6800
http://linked.open...iv/tvurceVysledku
  • Smékal, Zdeněk
  • Faúndez Zanuy, Marcos
  • Fabregas, Joan
  • Mekyska, Jiří
http://linked.open...n/vavai/riv/zamer
issn
  • 0302-9743
number of pages
http://localhost/t...ganizacniJednotka
  • 26220
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