VOICE RECOGNITION SECURITY SYSTEM USING MEL-FREQUENCY CEPSTRUM COEFFICIENTS - Mahalakshmi P; M, Muruganandam; A, Sharmila (Asian Journal of Pharmaceutical and Clinical Research, 2016)
ABSTRACT Objective: Voice Recognition is a fascinating field spanning several areas of computer science and mathematics. Reliable speaker recognition is a hard problem, requiring a combination of many techniques; however modern methods have been able to achieve an impressive degree of accuracy. The objective of this work is to examine various speech and speaker recognition techniques and to apply them to build a simple voice recognition system. Method: The project is implemented on software which uses different techniques such as Mel frequency Cepstrum Coefficient (MFCC), Vector Quantization (VQ) which are implemented using MATLAB. Results: MFCC is used to extract the characteristics from the input speech signal with respect to a particular word uttered by a particular speaker. VQ codebook is generated by clustering the training feature vectors of each speaker and then stored in the speaker database. Conclusion: Verification of the speaker is carried out using Euclidian Distance. For voice recognition we implement the MFCC approach using software platform MatlabR2013b. Keywords: Mel-frequency cepstrum coefficient, Vector quantization, Voice recognition, Hidden Markov model, Euclidean distance.