Unsupervised rapid speaker adaptation based on selective eigenvoice merging for user-specific voice interaction

Choi, Dong-Jin; Park, Jeong-Sik; Oh, Yung-Hwan

doi:10.1016/j.engappai.2015.01.010

Cited by 4 publications

(2 citation statements)

References 31 publications

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“…Biometrics may use physical or behavioral characteristics for identification purposes, and different alternatives have been explored over the years: fingerprint [3,4,5], hand geometry [6,7], palmprint [8], voice [9,10], face [11,12,13], and handwritten signature [14]. Among those, face stands out for its acceptability and recognition cost, turning out to be one of the best option for a wide range of applications, from low-security uses (e.g., social media and smartphone access control) to high-security applications (e.g., border control and video surveillance in critical places).…”

Section: Introductionmentioning

confidence: 99%

How far did we get in face spoofing detection?

Souza

Oliveira

Pamplona

et al. 2018

Engineering Applications of Artificial Intelligence

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The growing use of control access systems based on face recognition shed light over the need for even more accurate systems to detect face spoofing attacks. In this paper, an extensive analysis on face spoofing detection works published in the last decade is presented. The analyzed works are categorized by their fundamental parts, i.e., descriptors and classifiers. This structured survey also brings a comparative performance analysis of the works considering the most important public data sets in the field. The methodology followed in this work is particularly relevant to observe temporal evolution of the field, trends in the existing approaches, * Corresponding author: Luciano Oliveira, tel. +55 71 3283-9472Email addresses: luiz.otavio@ufba.br (Luiz Souza), lrebouca@ufba.br (Luciano Oliveira), mauricio@dcc.ufba.br (Mauricio Pamplona), papa@fc.unesp.br (Joao Papa) to discuss still opened issues, and to propose new perspectives for the future of face spoofing detection.

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Section: Introductionmentioning

confidence: 99%

How far did we get in face spoofing detection?

Souza

Oliveira

Pamplona

et al. 2018

Engineering Applications of Artificial Intelligence

View full text Add to dashboard Cite

show abstract

“…Finally, the SA model represents a model transformed from the SI model according to speaker adaptation procedures. The adaptation only requires a relatively small amount of data (called adaptation data) obtained from the user (called the target speaker), but produces the usercharacterized acoustic model, nearly achieving the performance of the SD model (Matsui and Furui, 1998;Choi et al, 2015).…”

Section: Introductionmentioning

confidence: 99%