I-Vector Multilayer Perceptron in Speaker Recognition System



Actually, i-vector space is the most recurrent representation of speech information in speaker recognition systems. The scoring process is generally based on Cosine Distance (CD) or Probablistic Linear Distriminant Analysis (PLDA) methods. The aim of this work is to replace these approaches by a MultiLayer? Perceptron (MLP). The MLP showed good performances in nonlinear function approximation. The main idea is to find better functions than cosine scoring method. The performance of the MLP method will be compared with other methods such as CD, PLDA and Restricted Boltzmann Machines (RBM) method presented by Jean Luc.