Now showing items 1-6 of 6

  • Deep belief networks for i-vector based speaker recognition 

    Ghahabi Esfahani, Omid; Hernando Pericás, Francisco Javier (Institute of Electrical and Electronics Engineers (IEEE), 2014)
    Conference report
    Restricted access - publisher's policy
    The use of Deep Belief Networks (DBNs) is proposed in this paper to model discriminatively target and impostor i-vectors in a speaker verification task. The authors propose to adapt the network parameters of each speaker ...
  • Deep learning for i-vector speaker and language recognition 

    Ghahabi Esfahani, Omid (Universitat Politècnica de Catalunya, 2018-05-29)
    Doctoral thesis
    Open Access
    Over the last few years, i-vectors have been the state-of-the-art technique in speaker and language recognition. Recent advances in Deep Learning (DL) technology have improved the quality of i-vectors but the DL techniques ...
  • Deep neural networks for i-vector language identification of short utterances in cars 

    Ghahabi Esfahani, Omid; Bonafonte Cávez, Antonio; Hernando Pericás, Francisco Javier; Moreno Bilbao, M. Asunción (International Speech Communication Association (ISCA), 2016)
    Conference report
    Restricted access - publisher's policy
    This paper is focused on the application of the Language Identification (LID) technology for intelligent vehicles. We cope with short sentences or words spoken in moving cars in four languages: English, Spanish, German, ...
  • Global impostor selection for DBNs in multi-session i-vector speaker recognition 

    Ghahabi Esfahani, Omid; Hernando Pericás, Francisco Javier (2014-11-19)
    Article
    Restricted access - publisher's policy
    An effective global impostor selection method is proposed in this paper for discriminative Deep Belief Networks (DBN) in the context of a multi-session i-vector based speaker recognition. The proposed method is an ...
  • i-Vector modeling with deep belief networks for multi-session speaker recognition 

    Ghahabi Esfahani, Omid; Hernando Pericás, Francisco Javier (2014)
    Conference report
    Restricted access - publisher's policy
    In this paper we propose an impostor selection method for a Deep Belief Network (DBN) based system which models i-vectors in a multi-session speaker verification task. In the proposed method, instead of choosing a ...
  • On the acoustic environment of a neonatal intensive care unit: initial description, and detection of equipment alarms 

    Raboshchuk, Ganna; Nadeu Camprubí, Climent; Ghahabi Esfahani, Omid; Solvez, Sergi; Muñoz Mahamud, Blanca; Riverola de Veciana, Ana; Navarro Hervas, Santiago (International Speech Communication Association (ISCA), 2014)
    Conference lecture
    Restricted access - publisher's policy
    The acoustic environment of a typical neonatal intensive care unit (NICU) is very rich and may contain a large number of different sounds, which come either from the equipment or from the human activities taking place in ...