Robustness Study of Free-Text Speaker Identification and Verification
Baras, John, S.
Date: April 27 - April 30, 1993
Usable free-text speaker identification and voice verification systems must exhibit robustness under varying operational conditions. We study the degree of robustness provided by various signal processing techniques    by experimenting on a widely used long distance telephone data base   . This data base consists of data recorded at two different sites, with data from one site much poorer in quality than the other; further, the recording equipment had been inadvertly changed for the later half of the sessions resulting in a significantly changed environment. Our study identifies the combination of techniques that provide consistent and significant improvements; our results surpass other published results    on the same task. Specifically, in the task of identifying 16 speakers, with training data from the recording prior to equipment change and testing on data from a set after the change(the most challenging condition), we obtain a correct identification rate of 87.5% with an average rank of 1.12;  obtains the hitherto best result of 75% correct identification with an average rank of 1.56: without any robustness processing, the rate was only 12%. Detailed results on exhaustive experimentation are presented along with appropriate discussions.