Now showing items 1-6 of 6

  • Deep learning backend for single and multisession i-vector speaker recognition 

    Ghahabi, Omid; Hernando Pericás, Francisco Javier (2017-04-01)
    Article
    Open Access
    The lack of labeled background data makes a big performance gap between cosine and Probabilistic Linear Discriminant Analysis (PLDA) scoring baseline techniques for i-vectors in speaker recognition. Although there are some ...
  • Feature classification by means of Deep Belief Networks for speaker recognition 

    Safari, Pooyan; Ghahabi, Omid; Hernando Pericás, Francisco Javier (Institute of Electrical and Electronics Engineers (IEEE), 2015)
    Conference report
    Restricted access - publisher's policy
    In this paper, we propose to discriminatively model target and impostor spectral features using Deep Belief Networks (DBNs) for speaker recognition. In the feature level, the number of impostor samples is considerably ...
  • From features to speaker vectors by means of restricted Boltzmann machine adaptation 

    Safari, Pooyan; Ghahabi, Omid; Hernando Pericás, Francisco Javier (2016)
    Conference lecture
    Open Access
    Restricted Boltzmann Machines (RBMs) have shown success in different stages of speaker recognition systems. In this paper, we propose a novel framework to produce a vector-based representation for each speaker, which will ...
  • Restricted Boltzmann machines for vector representation of speech in speaker recognition 

    Ghahabi, Omid; Hernando Pericás, Francisco Javier (Elsevier, 2018-01)
    Article
    Open Access
    Over the last few years, i-vectors have been the state-of-the-art technique in speaker recognition. Recent advances in Deep Learning (DL) technology have improved the quality of i-vectors but the DL techniques in use are ...
  • Restricted Boltzmann Machine Supervectors for speaker recognition 

    Ghahabi, Omid; Hernando Pericás, Francisco Javier (Institute of Electrical and Electronics Engineers (IEEE), 2015)
    Conference report
    Restricted access - publisher's policy
    The use of Restricted Boltzmann Machines (RBM) is proposed in this paper as a non-linear transformation of GMM supervectors for speaker recognition. It will be shown that the RBM transformation will increase the discrimination ...
  • Speaker recognition by means of restricted Boltzmann machine adaptation 

    Safari, Pooyan; Ghahabi, Omid; Hernando Pericás, Francisco Javier (Universidad Autónoma de Madrid, 2016)
    Conference lecture
    Open Access
    Restricted Boltzmann Machines (RBMs) have shown success in speaker recognition. In this paper, RBMs are investigated in a framework comprising a universal model training and model adaptation. Taking advantage of RBM ...