Development of novel system for speaker verification

تاریخ : ستمبر ۲۰۱۵ - جون ۲۰۱٦

Speaker Recognition is the computing task of validating a user’s claimed identity using characteristics extracted from their voices. This technique is one of the most useful and popular biometric recognition techniques in the world especially related to areas in which security is a major concern. It can be used for authentication, surveillance, forensic speaker recognition and a number of related activities. Speaker recognition can be classified into identification and verification. Speaker identification is the process of determining which registered speaker provides a given utterance. Speaker verification, on the other hand, is the process of accepting or rejecting the identity claim of a speaker. The process of Speaker recognition consists of 2 modules namely: - feature extraction and feature classifying. Feature extraction is the process in which we extract a small amount of data from the voice signal that can later be used to represent each speaker. Feature classifying is the process 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 Artificial Neural Network (CGPANN)