Text-independent speaker verification is an interesting task where the use of Gaussian Mixture Models is almost a must. Nevertheless, some preliminar encouraging results obtained in previous works using ANN in speaker verification have led us to consider to perform a direct comparison between these different methods. In this sense, this paper is only focused on the classification stage of both GMM-based and ANNbased speaker verification systems. Experiments are accomplish making use of the AHUMADA/GAUDI spanish speech database, specially oriented for speaker-recognition tasks as it contains multisession and multichannel data of about 500 speakers. Results confirm a better performance when using GMM-based system and microphonic speech but, on the other hand, when testing in specific conditions and with real telephone speech ANN outperforms GMM results.