The task of identifying humans by their voice seems to be an easy task for human beings as people interact with a particular person, their mind is upskilled with that voice and the brain becomes proficient enough to easily recognize that particular voice next time. Using this human mind concept, the structure is designed and implemented. In the proposed system Convolutional Neural Network (CNN) has been used. 110 voice samples from 11 different participants/speakers have been collected. These voice signals were converted into the form of an image of the signal spectrogram. 90% of data were used for training and the remaining 10% was used for testing. Implementation was done in RStudio with R programming language. The system achieved 82% accuracy. The proposed system is facile and lucrative.

Convolutional neural network, speaker recognition, Keras, voice signal spectrogram, tuneR

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