A robust speaker recognition system based on dynamic time wrapping

Abstract The application relates to a robust speaker recognition system based on dynamic time wrapping. This invention lies in the field of voice recognition, specifically speaker recognition, and illustrates the basic principle and key technology including MFCC, DTW and so on. The invention consists of the following steps: To begin with, we collect some data and divide them into training set and test set. Secondly, in training procedure training data is preprocessed and converted into MFCCs, then stored in database. Thirdly, in test procedure, we process test data in the same way to get their MFCCs and compare them with those in database to get the result. With some improvement to the traditional endpoint detection method, this invention is more robust against noise when extracting effective speech segments and achieves 100% accuracy with our dataset, with 311.0524 seconds spent on recognition of each sample on average. Besides, the implementation in MATLAB is given. Generally speaking, this invention is a reliable tool to be used in police offices, banking systems, and other places that need speaker recognition. Training Training database data H procedur~eH Data Test Test data procedure Speaker Speaker4 ,,F E akerlResult Speaker2 Speaker5 Speaker3 Speaker6 Fig.1 Test data Training data J Judging effective speech segment Judging effective speech segment Calculation of MFCC Calculation of MFCC Comparison using DTW Save the results to the 1 t 1 database Gettheresults Fig.2 Fig.3