Modified gammatone frequency cepstral coefficients to improve spoofing detection

Voice spoofing is one of the major challenges that needs to be addressed in the development of robust speaker verification (SV) systems. Therefore, it is necessary to develop systems (spoofing detectors) that are able distinguish between genuine and spoofed speech utterances. In this work, we propose the use of modified gammatone frequency cepstral coefficients (MGFCC) on enhancing the performance of spoofing detection. We also compare the effectiveness of GMM based spoofing detectors developed using mel frequency cepstral coefficients (MFCC), gammatone frequency cepstral coefficients (GFCC), modified group delay cepstral coefficients (MGDCC) and cosine normalized phase cepstral coefficients (CNPCC) with that of MGFCC. The experimental results on ASV spoof 2015 database show that MGFCC outperforms magnitude based, MFCC and GFCC, and phase based, MGDCC and CNPCC, features on the known attack conditions. Further, we performed a score level fusion of the systems developed using MFCC, MGFCC, MGDCC and CNPCC. It is observed that the fused system significantly outperforms all the individual systems for known and unknown attack conditions of ASV spoof 2015 database.