Attributes | Values |
---|
rdf:type
| |
Description
| - 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
| |
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
| |
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
| |
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
| |
http://linked.open...iv/tvurceVysledku
| - Smékal, Zdeněk
- Faúndez Zanuy, Marcos
- Fabregas, Joan
- Mekyska, Jiří
|
http://linked.open...n/vavai/riv/zamer
| |
issn
| |
number of pages
| |
http://localhost/t...ganizacniJednotka
| |
is http://linked.open...avai/riv/vysledek
of | |