This paper presents a preliminary study on the use of the Factor Analysis (FA) methods in an automatic speaker diarization process, dedicated to the meeting rooms. Indeed , the speaker diarization process, based on the top-down E-HMM approach, integrates a FA-based speaker modeling in an additional resegmentation step, which aims at helping the refinement of the output segmenta-tion. Classically applied in speaker recognition to deal with channel variability issues, two main schemes of the FA application are proposed here: to deal with the (1) inter-speaker variability and with (2) the inter-segment variability. Different kinds of experiments have been conducted on the dataset of the last NIST/RT'09 evaluation campaign, leading to very interesting and promising results. For instance, they show that the couple of schemes proposed in this paper obtained competitive performance , compared to the baseline process, despite the small amount of development data used in this paper for the FA parameter estimation. Unexpectedly, they tend to show that the inter-segment variability component can be helpful for speaker diarization.