Exploració per autor "Ghahabi Esfahani, Omid"

Ara es mostren els items 1-12 de 12

    • Deep belief networks for i-vector based speaker recognition 

      Ghahabi Esfahani, Omid; Hernando Pericás, Francisco Javier (Institute of Electrical and Electronics Engineers (IEEE), 2014)
      Text en actes de congrés
      Accés restringit per política de l'editorial
      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 backend for single and multisession i-vector speaker recognition 

      Ghahabi Esfahani, Omid; Hernando Pericás, Francisco Javier (2017-04-01)
      Article
      Accés obert
      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 ...

    • Deep learning for i-vector speaker and language recognition 

      Ghahabi Esfahani, Omid (Universitat Politècnica de Catalunya, 2018-05-29)
      Tesi
      Accés obert
      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)
      Text en actes de congrés
      Accés restringit per política de l'editorial
      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, ...

    • Feature classification by means of Deep Belief Networks for speaker recognition 

      Safari, Pooyan; Ghahabi Esfahani, Omid; Hernando Pericás, Francisco Javier (Institute of Electrical and Electronics Engineers (IEEE), 2015)
      Text en actes de congrés
      Accés restringit per política de l'editorial
      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 Esfahani, Omid; Hernando Pericás, Francisco Javier (2016)
      Comunicació de congrés
      Accés obert
      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 ...

    • Global impostor selection for DBNs in multi-session i-vector speaker recognition 

      Ghahabi Esfahani, Omid; Hernando Pericás, Francisco Javier (2014-11-19)
      Article
      Accés restringit per política de l'editorial
      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)
      Text en actes de congrés
      Accés restringit per política de l'editorial
      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)
      Comunicació de congrés
      Accés restringit per política de l'editorial
      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 ...

    • Restricted Boltzmann Machine Supervectors for speaker recognition 

      Ghahabi Esfahani, Omid; Hernando Pericás, Francisco Javier (Institute of Electrical and Electronics Engineers (IEEE), 2015)
      Text en actes de congrés
      Accés restringit per política de l'editorial
      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 ...

    • Restricted Boltzmann machines for vector representation of speech in speaker recognition 

      Ghahabi Esfahani, Omid; Hernando Pericás, Francisco Javier (Elsevier, 2018-01)
      Article
      Accés obert
      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 ...

    • Speaker recognition by means of restricted Boltzmann machine adaptation 

      Safari, Pooyan; Ghahabi Esfahani, Omid; Hernando Pericás, Francisco Javier (Universidad Autónoma de Madrid, 2016)
      Comunicació de congrés
      Accés obert
      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 ...