Voice Biometrics

González-Rodríguez, Joaquín; Toledano, Doroteo T.; Ortega‐Garcia, Javier

doi:10.1007/978-0-387-71041-9_8

Cited by 13 publications

(5 citation statements)

References 43 publications

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“…In most of the cases, both sessions were acquired with the provided PC. Note that the speech information acquired enables both text-dependent (PINs) and text-independent speaker recognition experiments [27]. Digits are the same between sessions, enabling text-dependent speaker recognition based on digits.…”

Section: Data Set 1 (Ds1)-internetmentioning

confidence: 99%

The Multiscenario Multienvironment BioSecure Multimodal Database (BMDB)

Ortega‐Garcia¹,

Fiérrez²,

Alonso‐Fernandez³

et al. 2010

IEEE Trans. Pattern Anal. Mach. Intell.

207

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Abstract-A new multimodal biometric database designed and acquired within the framework of the European BioSecure Network of Excellence is presented. It is comprised of more than 600 individuals acquired simultaneously in three scenarios: 1) over the Internet, 2) in an office environment with desktop PC, and 3) in indoor/outdoor environments with mobile portable hardware. The three scenarios include a common part of audio/video data. Also, signature and fingerprint data have been acquired both with desktop PC and mobile portable hardware. Additionally, hand and iris data were acquired in the second scenario using desktop PC. Acquisition has been conducted by 11 European institutions. Additional features of the BioSecure Multimodal Database (BMDB) are: two acquisition sessions, several sensors in certain modalities, balanced gender and age distributions, multimodal realistic scenarios with simple and quick tasks per modality, cross-European diversity, availability of demographic data, and compatibility with other multimodal databases. The novel acquisition conditions of the BMDB allow us to perform new challenging research and evaluation of either monomodal or multimodal biometric systems, as in the recent BioSecure Multimodal Evaluation campaign. A description of this campaign including baseline results of individual modalities from the new database is also given. The database is expected to be available for research purposes through the BioSecure Association during 2008.

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Section: Data Set 1 (Ds1)-internetmentioning

confidence: 99%

The Multiscenario Multienvironment BioSecure Multimodal Database (BMDB)

Ortega‐Garcia¹,

Fiérrez²,

Alonso‐Fernandez³

et al. 2010

IEEE Trans. Pattern Anal. Mach. Intell.

207

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“…(see Refs. [1,2] for a survey of recent results). One important focal point of research is represented by the testing methodologies used to check the accuracy of voice biometrics solutions across the phonetic spectrum of a given language, which is particularly important in the case of text-independent solutions).…”

Section: Introductionmentioning

confidence: 99%

Rank-frequency distributions of Romanian words

Cocioceanu

Raportaru

Nicolin

et al. 2017

AIP Conference Proceedings

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Abstract. The calibration of voice biometrics solutions requires detailed analyses of spoken texts and in this context we investigate by computational means the rank-frequency distributions of Romanian words and word series to determine the most common words and word series of the language. To this end, we have constructed a corpus of approximately 2.5 million words and then determined that the rank-frequency distributions of the Romanian words, as well as series of two, and three subsequent words, obey the celebrated Zipf law.

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“…It has been noted that the use of SI could be of significant value here, in the form of a watch-list of 'known' voices against which each incoming call is checked for a match [6,10]. As with current methods, this type of detection could only be used to prevent repeat fraud where the first instance of fraud is detected by other means, for example, the specialist fraud team.…”

Section: Introductionmentioning

confidence: 99%

Effective speaker spotting for watch‐list detection of fraudsters in telephone banking

2015

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This study describes a special-case application of speaker recognition in open-set speaker-identification mode, which nonetheless has wide applicability. Watch-list based speaker spotting in telephone banking can potentially provide valuable protection against 'known' fraudsters with access to stolen customer details. In this study, the detection of known fraudsters in a telephone banking service using commercial off-the-shelf verification engines is described. A new 'delta scoring' method for watch-list detection is proposed based on using the genuine customer model as a reference. The approach combines for the first time speaker recognition in both verification and identification mode. Empirical experiment results show a significant gain in performance using the new method.

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Voice Biometrics

Cited by 13 publications

References 43 publications

The Multiscenario Multienvironment BioSecure Multimodal Database (BMDB)

The Multiscenario Multienvironment BioSecure Multimodal Database (BMDB)

Rank-frequency distributions of Romanian words

Effective speaker spotting for watch‐list detection of fraudsters in telephone banking

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