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MEKYSKA, J. FAÚNDEZ ZANUY, M. SMÉKAL, Z. FABREGAS, J.
Originální název
Score Fusion in Text-Dependent Speaker Recognition Systems
Typ
článek v časopise - ostatní, Jost
Jazyk
angličtina
Originální abstrakt
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 (three 3 s training samples per speaker).
Klíčová slova
text-dependent speaker recognition, voice imprint, fractional distances, biometric dispersion matcher, dynamic time warping
Autoři
MEKYSKA, J.; FAÚNDEZ ZANUY, M.; SMÉKAL, Z.; FABREGAS, J.
Rok RIV
2011
Vydáno
24. 11. 2011
Nakladatel
Springer
ISSN
0302-9743
Periodikum
Lecture Notes in Computer Science
Ročník
6800
Číslo
12
Stát
Spolková republika Německo
Strany od
120
Strany do
132
Strany počet
13
BibTex
@article{BUT75059, author="Jiří {Mekyska} and Marcos {Faúndez Zanuy} and Zdeněk {Smékal} and Joan {Fabregas}", title="Score Fusion in Text-Dependent Speaker Recognition Systems", journal="Lecture Notes in Computer Science", year="2011", volume="6800", number="12", pages="120--132", issn="0302-9743" }