This paper proposes features based on parametric representation of Fourier phase of speech for speaker verification. Direct computation of Fourier phase suffers from phase wrapping and hence we attempt parametric modelling of phase spectrum using an allpass (AP) filter. The coefficients of the AP filter are estimated by minimizing an entropy based objective function motivated from speech production process. The AP cepstral coefficients (APCC) derived from the group delay response of estimated AP filter are used as features for speaker verification. An i-vector based speaker verification system is employed to evaluate the performance of the proposed APCC features on NIST 2003 speaker recognition evaluation database. The equal error rates (EER) obtained from speaker verification systems built using APCC features and baseline mel-frequency cepstral coefficients (MFCC) are reported. A relative improvement of 12% was obtained overMFCC features by combining evidences from both MFCC and APCC based systems. © Odyssey 2014: Speaker and Language Recognition Workshop. All rights Reserved.