A Text–Independent Speaker Identification System Based on the Zak Transform

A novel text-independent speaker identification system based on the Zak transform is implemented. The data used in this paper are drawn from the ELSDSR database.The efficiency of identification approaches 91.3% using a single test file and 100% using two test files. The method shows comparable efficiency results with the well known MFCC method with an advantage of being faster in both modeling and identification.