Faheem Ullah
, Dr. Muhammad Irfan Khattak, Muhammad Israr, Khushal Khan, Naveed Ur Rehman, Muhammad Zia
Speaker Recognition is the work out obligation of authorizing a user’s demanded identity using physiognomies removed from their voices. This skill is one of the supreme valuable and standard biometric recognition practices in the world chiefly linked to zones in which security is a foremost concern. It can be used for confirmation, investigation, surveillance, reconnaissance, authentication, forensic speaker recognition and a numeral of associated accomplishments. Speaker recognition can be categorized into identification and verification. Speaker identification is the technique of influencing which registered speaker delivers an assumed utterance. Speaker verification, in contrast, is the technique of accepting or discarding the identity claim of a speaker. The progression of Speaker recognition involves of two segments i.e. feature extraction and feature classifying. Feature extraction is the method in which we extract a minor expanse of data from the voice signal that can be used in future to indicate each speaker. Feature classifying is the procedure of familiarize the system with features. Our proposed work consists of feature extraction from the voices of speakers through Mel frequency Cepstral Coefficients (MFCC) and classifying them by Cartesian Genetic Programing (CGP) to get an efficient logic gates circuit and by Cartesian Genetic Programing Evolved Artificial Neural Network (CGP-E-ANN) to develop an efficient and novel system for speaker verification.
Faheem Ullah Dr. Muhammad Irfan Khattak Muhammad Israr Khushal Khan Naveed Ur Rehman Muhammad Zia “Speaker Verification System Based On Cartesian Genetic Programming (CGP) and Cartesia International Journal of Engineering Works Vol. 9 Issue 09 PP. 166-172 September 2022. https://doi.org/10.34259/ijew.22.909166172.
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