In this paper a speaker dependent cohort selection for T-norm score normalization is proposed in the context of text-dependent speaker verification. The goal of the proposed technique is to find a set of cohort speakers who are close to the target speaker. In order to properly select the subset of speakers for the normalization, a distance between each target speaker model and the the available normalization models is computed and the nearest models are chosen to represent the cohort set for that target model. The proposed system is evaluated on Part1 of the RSR2015 database. With the proposed normalization method a relative improvement of 71% in terms of the Equal Error Rater (EER) is achieved.