Enhancing Voice Print using Computer Vision through Optical Character Recognition with Subscriber Identity Module


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

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.

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