Different aspects of source information for limited data speaker verification

Abstract

Limited data speaker verification has shown its significance in practical system oriented applications. The paper shows the importance of different aspects of voice source feature for limited test data scenario. A baseline speaker verification system using conventional mel frequency cepstral co-efficients (MFCC) feature is developed and performance under limited test data condition (≤10 s) is evaluated. A parallel system based on source feature mel power difference of spectrum in subband (M-PDSS) is developed in the i-vector based speaker verification framework. Both the systems were fused at the score level for the cases of short segments of test speech, which demonstrated the importance of source feature with reduction in test data duration. A comparative study of the M-PDSS feature is then made with our earlier work using discrete cosine transform of the integrated linear prediction residual (DCTILPR) feature and then fusion of two source features M-PDSS and DCTILPR along with MFCC features is carried out. An absolute improvement of 5.19% is obtained for 2 s of test data which conveys the significance of multiple source information under limited data speaker verification as it carries different aspects of source information.