1. A speaker recognition system adapted for receiving audio data, the system being adapted for: receiving audio data under test; obtaining a Medium Frequency Relative Energy (MF) parameter, comprising a ratio between an energy of the received audio data under test in a predetermined frequency band and an energy of a complete frequency spectrum of the received audio data under test; and classifying using a Gaussian classifier whether the received audio data under test is genuine or represents a recording replayed through a loudspeaker, based on the Medium Frequency Relative Energy (MF) parameter, wherein the Gaussian classifier is trained by the following steps: a first Gaussian is obtained by: receiving genuine audio data; obtaining a first Medium Frequency Relative Energy (MF) parameter, comprising the ratio between the energy of the genuine audio data in a predetermined frequency band and the energy of the complete frequency spectrum of the genuine audio data; receiving audio data representing recordings replayed through a loudspeaker; and modelling the genuine audio data; and wherein a second Gaussian is obtained by: receiving audio data representing recordings replayed through a loudspeaker; obtaining a second Medium Frequency Relative Energy (MF) parameter, comprising the ratio between the energy of the audio data representing recordings replayed through a loudspeaker in a predetermined frequency band and the energy of the complete frequency spectrum of the audio data representing recordings replayed through a loudspeaker; and modelling the audio data representing recordings replayed through a loudspeaker with a second Gaussian.