Speech Recognition Using MFCC and VQLBG - M. Suman; K. Harish; K. Manoj Kumar; S. Samrajyam (Institute of Advanced Engineering and Science, 2015)
Speaker Recognition is the computing task of confirmatory a user’s claimed identity mistreatment characteristics extracted from their voices. This technique is one of the most helpful and in style biometric recognition techniques in the world particularly connected to areas in that security could be a major concern. It are often used for authentication, police work, rhetorical speaker recognition and variety of connected activities. The method of Speaker recognition consists of two modules particularly feature extraction and have matching. Feature extraction is that the method during which we have a tendency to extract a tiny low quantity of knowledge from the voice signal that will later be used to represent every speaker. Feature matching involves identification of the unknown speaker by scrutiny the extracted options from his/her voice input with those from a collection of identified speakers. Our projected work consists of truncating a recorded voice signal, framing it, passing it through a window perform, conniving the Short Term FFT, extracting its options and Matching it with a hold on guide. Cepstral constant Calculation and Mel frequency Cepstral Coefficients (MFCC) area unit applied for feature extraction purpose.VQLBG (Vector Quantization via Linde-Buzo-Gray) algorithmic rule is used for generating guide and feature matching purpose.