1 / 23

Using Speaker Recognition

Using Speaker Recognition. Judith A. Markowitz, PhD J. Markowitz, Consultants Chicago, IL www.jmarkowitz.com. AVIOS-Israel Annual Meeting May 15, 2007. What is Speaker Recognition?. A group of biometric technologies that analyze information

merrill-salas
Download Presentation

Using Speaker Recognition

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. Using Speaker Recognition Judith A. Markowitz, PhD J. Markowitz, Consultants Chicago, IL www.jmarkowitz.com AVIOS-Israel Annual Meeting May 15, 2007

  2. What is Speaker Recognition? A group of biometric technologies that analyze information from the stream of speech

  3. What Speaker Recognition Does • verify a claim of identity (verification) • identify the speaker (identification) • put the speaker into a group/category (classification) • perform other speaker-centric tasks Müller, C., ed. Speaker Classification Volume 4343 & Volume 4441 of Lecture Notes in Computer Science / Artificial Intelligence. Springer, Heidelberg - Berlin - New York (2007).

  4. Speaker Verification • Enrollment • Verification Two-step process

  5. Speaker Verification • Validate enrollee’s identity (authenticity) • Collect samples • Create model (reference model) • Store securely (integrity) Enrollment

  6. Speaker Verification • Claim of identity • User input • Create Model • Retrieve reference model • Matching = One-to-one comparison • Decision= Accept / Reject / Undecided Verification

  7. Claim of Identity

  8. User Input • Password (text dependent) • Challenge-response (text prompted) • Free speech (text independent) Three Main Types

  9. Password

  10. Challenge Response

  11. Multiple AIRS Airplane Cockpit Security • Access to cockpit (SV - text-dependent) • Monitoring of speakers via headsets (SV-text independent) • “Acoustic monitoring” Embedded in cockpit (SI)

  12. Language Independent

  13. Language Dependent

  14. Model Creation & Matching Algorithms • Hidden Markov models • Gaussian classifiers • Neural network • Other

  15. Does SV Work? National Physical Laboratory of the UK Mansfield, Anthony J. & Wayman, James L. 2002 Best Practices in Testing and Reporting Performance of Biometric Devices. Version 2.01. Centre for Mathematics and Scientific Computing Teddington, UK: National Physical Laboratory

  16. Does SV Work? University of Canberra Tests Test 2006* 2005** Persay Persay Nuance Commercial alpha Verifier Counting 1-9 1.05 0.77 0.91 Names 3.74 3.78 5.13 * University of Canberra 2006 PERSAY TECHNOLOGY EVALUATION RESULTS ** University of Canberra 2005 SPEAKER VERIFICATION EVALUATION REPORT Scientific evaluation of speaker verification technologies on behalf of Australian Government Document No: SVE Test Report Version 2.0 Project ID: RFP-SV-026f

  17. Does SV Work? • Mimics • Tape recorders • Noise • Channel & Device Mismatch Challenges- Real and Imagined Most identical to problems facing ASR

  18. Password Reset • Organizations

  19. IVR/Self service • Organizations

  20. Radica Non-IVR Transactions • Organizations

  21. What Is Next? • Multi-factor authentication • Standards • Linguistic elements http://www.voicexml.org/resources/biometrics

  22. Thank you QUESTIONS?

More Related