Introduction to voice presentation attack detection and recent advances

Md Sahidullah, Hector Delgado, Massimiliano Todisco, Tomi Kinnunen, Nicholas Evans, Junichi Yamagishi and Kong-Aik Lee
Book chapter N°15 of "Handbook of Biometric Anti-Spoofing: Presentation Attack Detection"; Springer Marcel, S., Nixon, M.S., Fierrez, J., Evans, N. (Eds.); Springer, 2018

Over the past few years significant progress has been made in the field
of presentation attack detection (PAD) for automatic speaker recognition (ASV).
This includes the development of new speech corpora, standard evaluation protocols
and advancements in front-end feature extraction and back-end classifiers. The
use of standard databases and evaluation protocols has enabled for the first time
the meaningful benchmarking of different PAD solutions. This chapter summarises
the progress, with a focus on studies completed in the last three years. The article
presents a summary of findings and lessons learned from two ASVspoof challenges,
the first community-led benchmarking efforts. These show that ASV PAD remains
an unsolved problem and that further attention is required to develop generalised PAD solutions which have potential to detect diverse and previously unseen spoofing
attacks.

DOI
HAL
Type:
Ouvrage
Date:
2018-09-11
Department:
Sécurité numérique
Eurecom Ref:
5668
Copyright:
© Springer. Personal use of this material is permitted. The definitive version of this paper was published in Book chapter N°15 of "Handbook of Biometric Anti-Spoofing: Presentation Attack Detection"; Springer Marcel, S., Nixon, M.S., Fierrez, J., Evans, N. (Eds.); Springer, 2018 and is available at : http://doi.org/10.1007/978-3-319-92627-8_15

PERMALINK : https://www.eurecom.fr/publication/5668