LOW POWER, SMALL FOOT PRINT EMBEDDED VOICE BIOMETRICS SYSTEM

Authors

  • Puja Ramesh Chaudhari
  • John Sahaya Rani Alex

Keywords:

—Speaker Recognition, MFCC, Biometrics, Voice, HMM.

Abstract

Biometrics is indeed becoming an important solution for any highly secured system. Voice is one of the biometric parameters
that can use for a person identification and verification. In this paper, a small foot-print, low power embedded system is
proposed and implemented using Beagle Bone Black (BBB). Hidden Markov Model (HMM) based speaker recognition system
is implemented. Mel-Frequency Cepstrum Coefficients (MFCC) is used as features to identify the speaker. Each speaker is
modelled as one HMM. The verification of the speaker voice is done using Viterbi decoder. The embedded system for Voice
Biometric system is successfully implemented for a limited number of speakers and the accuracy is verified to be as almost
100%

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Published

2021-03-31

How to Cite

Chaudhari, P. R. ., & Alex, J. S. R. . (2021). LOW POWER, SMALL FOOT PRINT EMBEDDED VOICE BIOMETRICS SYSTEM. Pakistan Journal of Biotechnology, 13(special issue 1), 121–124. Retrieved from https://pjbt.org/index.php/pjbt/article/view/251

Issue

Vol. 13 No. special issue 1 (2016): Pak. J. Biotechnology.(special issue)

Section

Research Articles