Abstract
In this paper, we explore new methods by which speakers can be identified and discriminated, using features derived from the fourier transform phase. The Modified Group Delay Feature (MODGDF) which is a parameterized form of the modified group delay function is used as a front end fea- ture in this study. A Gaussian mixture model (GMM) based speaker identification system is built with the MODGDF as the front end feature. The system is tested on both clean (TIMIT) and noisy telephone (NTIMIT) speech. The results obtained are compared with traditional Mel frequency cepstral coefficients (MFCC) which is derived from the fourier transform magnitude. When both MFCC and MODGDF were combined, the performance improved by about 4 pct. indicating that both phase and magnitude contain complementary information. […]
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