Evaluation of Voice Biometrics for Identification and Authentication 2021-01-0262
The work presented here is part of the research done in the field of voice biometrics. This paper helps to understand the state-of-the-art in speaker recognition technology potentially capable of solving challenges related to speaker identification (to identify a speaker among multiple speakers) and speaker verification/authentication (to recognize the current speaking person at a pre-defined access level and authenticate accordingly). The research was focused on performing an unbiased evaluation of two individual voice biometric services. The level of accuracy in identifying and authenticating individuals using these services provides an insight into the current state of technology and the state of what other dual authentication methods could be used to achieve a desired True Acceptance Rate (TAR) and False Acceptance Rates (FAR).
Several factors like: complexity, ease of use for enrollment, effect of background noise, distance from microphone, and length of authentication speech, were considered in order to evaluate the technology for interior/exterior use cases. A generic strategy was designed to evaluate the services using the same test conditions. Obtaining false acceptance rates lead to further study of the need for a dual authentication system for business-critical use cases (e.g., payment transactions, authorized entry into a vehicle) and non-critical business use cases (e.g., personalized audio/seat settings, suggestions, general queries, etc.)
This research showed that enrollment can be done on random speech and that lower number of enrollees is better for speaker identification. It was also determined that signal to noise ratio (SNR) and distance from microphone have a significant effect on speaker identification. In business-critical use cases, it was concluded that voice biometric technology cannot be used as a standalone authentication method and needs to be paired with other authentication methods like facial recognition, passwords, vein recognition, etc., along with voice for secure authentication.
Citation: Bekkanti, N., Busch, L., and Amman, S., "Evaluation of Voice Biometrics for Identification and Authentication," SAE Technical Paper 2021-01-0262, 2021, https://doi.org/10.4271/2021-01-0262. Download Citation
Author(s):
Nikhitha Bekkanti, Leah Busch, Scott Amman
Affiliated:
Ford Motor Company
Pages: 10
Event:
SAE WCX Digital Summit
ISSN:
0148-7191
e-ISSN:
2688-3627
Related Topics:
Noise measurement
Data exchange
Identification
Noise
Anthropometrics
Audio equipment
Research and development
Sound quality
Cardiovascular system
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