Authors :
SADO – ALIMIKHENA ELIZABETH; UMAR ADAM ISAH; ADOGA EMMANUEL ALEONOLU; OLOTU YAHAYA; GARUBA ISAH ANIRU
Volume/Issue :
Volume 7 - 2022, Issue 5 - May
Google Scholar :
https://bit.ly/3IIfn9N
Scribd :
https://bit.ly/3wKlrdP
DOI :
https://doi.org/10.5281/zenodo.6575226
Abstract :
This research focuses on voiceprint collection
of fully registered subscriber identity module using
Smartphone to generate computer coded language
inform of identification audio image signal text. It is
propagated at a speed of 4.21m/s, frequency 0.048HZ
and wavelength of 7083.3 λ through a vacuum to form
constructive wave signal with light source from the
Smartphone screen. At this point, a voice pattern with
word syllable stress with be captured and transmitted
into an articulated text binary value number with
digitizer to convert analog calls into digital barcode text.
The subscriber identity module card will be seal with the
user signature for further sequence and chart with fire
wall through an audio image signal feedback. This
process was made possible through smart phone location
notification street map summary. To generate accurate
biometric of recorded speech into an image for crime
scrutiny. The optical character recognition efficacy was
merged with fingerprint call answering mode which act
a synchronous biometric. So that, deep learning and
convolutional neural network work out solutions with
the algorithm to differentiate true tone from fake tone
by air flow, air filter and audible pulses to know the
exact caller for identity through vocal tract to reduce
crime rate with the aid of internet cloud.
Keywords :
Voiceprint, Computer Vision, Optical Character Recognition, Subscriber Identity Module.
This research focuses on voiceprint collection
of fully registered subscriber identity module using
Smartphone to generate computer coded language
inform of identification audio image signal text. It is
propagated at a speed of 4.21m/s, frequency 0.048HZ
and wavelength of 7083.3 λ through a vacuum to form
constructive wave signal with light source from the
Smartphone screen. At this point, a voice pattern with
word syllable stress with be captured and transmitted
into an articulated text binary value number with
digitizer to convert analog calls into digital barcode text.
The subscriber identity module card will be seal with the
user signature for further sequence and chart with fire
wall through an audio image signal feedback. This
process was made possible through smart phone location
notification street map summary. To generate accurate
biometric of recorded speech into an image for crime
scrutiny. The optical character recognition efficacy was
merged with fingerprint call answering mode which act
a synchronous biometric. So that, deep learning and
convolutional neural network work out solutions with
the algorithm to differentiate true tone from fake tone
by air flow, air filter and audible pulses to know the
exact caller for identity through vocal tract to reduce
crime rate with the aid of internet cloud.
Keywords :
Voiceprint, Computer Vision, Optical Character Recognition, Subscriber Identity Module.
