Location via proxy:   [ UP ]  
[Report a bug]   [Manage cookies]                
Skip to main content
SpringerLink
Log in

Anti-spoofing, Voice Databases

  • Reference work entry
  • First Online:
Encyclopedia of Biometrics

  • 150 Accesses

Synonyms

Speaker recognition corpora; Speaker recognition spoofing

Definition

As with any task involving statistical pattern recognition, the assessment of spoofing and anti-spoofing approaches for voice recognition calls for significant-scale databases of spoofed speech signals. Depending on the application, these signals should normally reflect spoofing attacks performed prior to acquisition at the sensor or microphone. Since the collection of large quantities of any biometric data is always extremely time consuming and cost prohibitive, and consistent with some telephony applications, almost all of the existing work to assess spoofing and anti-spoofing in voice recognition is performed with databases of speech signals subjected to post-sensor spoofing attacks. While such a setup can be justified, the lack of suitable sensor-level databases is a weakness in the research field. Additionally, whereas spoofing relates to authentication, and thus predominantly text-dependent scenarios,...

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution

Subscribe and save

Springer+ Basic
$34.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 899.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Hardcover Book
USD 549.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. N. Evans, T. Kinnunen, J. Yamagishi, Spoofing and countermeasures for automatic speaker verification, in Proceedings of INTERSPEECH, Lyon, 2013

    Google Scholar 

  2. Y.W. Lau, M. Wagner, D. Tran, Vulnerability of speaker verification to voice mimicking, in Proceedings of IEEE International Symposium on Intelligent Multimedia, Video and Speech Processing, Hong Kong, 2004, pp. 145–148

    Google Scholar 

  3. J. Lindberg, M. Blomberg, Vulnerability in speaker verification-a study of technical impostor techniques, in Proceedings of European Conference on Speech Communication and Technology, Budapest, vol. 3, 1999, pp. 1211–1214

    Google Scholar 

  4. N. Evans, T. Kinnunen, J. Yamagishi, Z. Wu, F. Alegre, P. De Leon, Voice anti-spoofing, in Handbook of Biometric Anti-spoofing, ed. by S. Marcel, S.Z. Li, M. Nixon (Springer-Verlag, London 2014)

    Google Scholar 

  5. T. Masuko, T. Hitotsumatsu, K. Tokuda, T. Kobayashi, On the security of HMM-based speaker verification systems against imposture using synthetic speech, in Proceedings of EUROSPEECH, Budapest, 1999

    Google Scholar 

  6. B.L. Pellom, J.H. Hansen, An experimental study of speaker verification sensitivity to computer voice-altered imposters, in IEEE Proceedings of the International Conference on Acoustics, Speech, and Signal Processing, Phoenix, vol. 2, 1999, pp. 837–840

    Google Scholar 

  7. F. Alegre, A. Amehraye, N. Evans, A one-class classification approach to generalised speaker verification spoofing countermeasures using local binary patterns, in Proceedings of International Conference on Biometrics: Theory, Applications and Systems, Washington, DC, 2013

    Google Scholar 

  8. D.B. Paul, J.M. Baker, The design for the Wall Street Journal-based CSR corpus, in Proceedings of the Workshop on Speech and Natural Language, Harriman, New York (Association for Computational Linguistics, 1992), pp. 357–362

    Google Scholar 

  9. P.L. De Leon, M. Pucher, J. Yamagishi, I. Hernaez, I. Saratxaga, Evaluation of speaker verification security and detection of HMM-based synthetic speech. IEEE Trans. Audio Speech Lang. Process. 20, 22802290 (2012)

    Google Scholar 

  10. A. Martin, Speaker databases and evaluation, in Encylopedia of Biometrics, ed. by S.Z. Li, A.K. Jain (Springer Science + Business Media, LLc 2009)

    Google Scholar 

  11. D. Matrouf, J.-F. Bonastre, C. Fredouille, Effect of speech transformation on impostor acceptance, in Proceedings of IEEE International Conference on Acoustics, Speech and Signal Processing, Toulouse, vol. 1, 2006

    Google Scholar 

  12. F. Alegre, A. Amehraye, N. Evans, Spoofing countermeasures to protect automatic speaker verification from voice conversion, in Proceedings of IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), Vancouver, 2013

    Google Scholar 

  13. Z. Wu, A. Larcher, K.A. Lee, E.S. Chng, T. Kinnunen, H. Li, Vulnerability evaluation of speaker verification under voice conversion spoofing: the effect of text constraints, in Proceedings of INTERSPEECH, Lyon, 2013

    Google Scholar 

  14. A. Larcher, K.A. Lee, B. Ma, H. Li, The RSR2015: database for text-dependent speaker verification using multiple pass-phrases, in Proceedings of INTERSPEECH, Portland, 2012

    Google Scholar 

  15. T. Kinnunen, Z.-Z. Wu, K.A. Lee, F. Sedlak, E.S. Chng, H. Li, Vulnerability of speaker verification systems against voice conversion spoofing attacks: the case of telephone speech, in Proceedings of IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), Prague, 2012, pp. 4401–4404

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. EURECOM, Campus SophiaTech, 450 Route des Chappes, 06410, Biot, France

    Nicholas Evans & Federico Alegre

  2. University of Eastern Finland (UEF), Tulliportinkatu 1, 80130, Joensuu, Finland

    Tomi Kinnunen

  3. Nanyang Technological University (NTU), 50 Nanyang Ave, 639798, Nanyang, Singapore

    Zhizheng Wu

  4. National Institute of Informatics, 2-1-2 Hitotsubashi, 101-0003, Chiyoda, Japan

    Junichi Yamagishi

  5. University of Edinburgh, Edinburgh, UK

    Junichi Yamagishi

Authors
  1. Nicholas Evans
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Federico Alegre
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Tomi Kinnunen
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Zhizheng Wu
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Junichi Yamagishi
    View author publications

    You can also search for this author in PubMed Google Scholar

Editor information

Editors and Affiliations

  1. Center for Biometrics and Security, Research & National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing, China

    Stan Z. Li

  2. Departments of Computer Science and Engineering, Michigan State University, East Lansing, MI, USA

    Anil K. Jain

Rights and permissions

Reprints and permissions

Copyright information

© 2015 Springer Science+Business Media New York

About this entry

Cite this entry

Evans, N., Alegre, F., Kinnunen, T., Wu, Z., Yamagishi, J. (2015). Anti-spoofing, Voice Databases. In: Li, S.Z., Jain, A.K. (eds) Encyclopedia of Biometrics. Springer, Boston, MA. https://doi.org/10.1007/978-1-4899-7488-4_9048

Download citation

Publish with us

Policies and ethics

Search

Navigation