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Published in:
An Introduction to Fingerprint Presentation Attack Detection Read chapter Read first chapter

2019 | OriginalPaper | Chapter

15. Introduction to Voice Presentation Attack Detection and Recent Advances

Authors : Md Sahidullah, Héctor Delgado, Massimiliano Todisco, Tomi Kinnunen, Nicholas Evans, Junichi Yamagishi, Kong-Aik Lee

Published in: Handbook of Biometric Anti-Spoofing

Publisher: Springer International Publishing

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Abstract

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 3 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.

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previous chapter Review of Face Presentation Attack Detection Competitions
next chapter A Cross-Database Study of Voice Presentation Attack Detection
Appendix
Available only for authorised users
Footnotes
7
A replay configuration refers to a unique combination of room, replay device and recording device while a session refers to a set of source files, which share the same replay configuration.
 
8
See Appendix A.2. Software packages.
 
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Metadata
Title
Introduction to Voice Presentation Attack Detection and Recent Advances
Authors
Md Sahidullah
Héctor Delgado
Massimiliano Todisco
Tomi Kinnunen
Nicholas Evans
Junichi Yamagishi
Kong-Aik Lee
Copyright Year
2019
Book
Handbook of Biometric Anti-Spoofing

Print ISBN: 978-3-319-92626-1

Electronic ISBN: 978-3-319-92627-8

Copyright Year: 2019

DOI
https://doi.org/10.1007/978-3-319-92627-8_15