Speaker recognition using pattern recognition neural network and feedforward neural network
نویسنده
چکیده
Neha Chauhan Birla Institute of Technology, Mesra, Ranchi Abstract— Speaker Recognition is the computing task of validating a user’s claimed identity using speech characteristics. Main objective of speech recognition system is to communication with a device through our voice. Mel frequency Cepstral Coefficient (MFCC) features are combined with pitch and root mean square values and tested for improvement in efficiency. Feed forward artificial neural network and pattern recognition neural network is used as a classifier. System was tested for 30 speakers. Better efficiency is obtained when MFCC features are combined with pitch and rms value over single MFCC features. Feed forward neural network gives better efficiency over pattern recognition neural network.70% of total samples are used for training and 30% of total samples are used for system testing. Simulation is done using matlab software. Accuracy of system is calculated using confusion matrix. .
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