Now showing items 1-11 of 11

    • A novel approach to real-time range estimation of underwater acoustic sources using supervised machine learning 

      Houégnigan, Ludwig; Safari, Pooyan; Nadeu Camprubí, Climent; Van der Schaar, Mike Connor Roger Malcolm; André, Michel (Institute of Electrical and Electronics Engineers (IEEE), 2017)
      Conference lecture
      Open Access
      The proposed paper introduces a novel method for range estimation of acoustic sources, both cetaceans and industrial sources, in deep sea environments using supervised learning with neural networks in the contex of a single ...
    • Deep Learning For Sequential Pattern Recognition 

      Safari, Pooyan (Universitat Politècnica de Catalunya / Technische Universität München, 2013-12-18)
      Master thesis
      Open Access
      Covenantee:   Technische Universität München
      In recent years, deep learning has opened a new research line in pattern recognition tasks. It has been hypothesized that this kind of learning would capture more abstract patterns concealed in data. It is motivated by the ...
    • Double multi-head attention for speaker verification 

      India Massana, Miquel Àngel; Safari, Pooyan; Hernando Pericás, Francisco Javier (Institute of Electrical and Electronics Engineers (IEEE), 2021)
      Conference report
      Open Access
      Most state-of-the-art Deep Learning systems for text-independent speaker verification are based on speaker embedding extractors. These architectures are commonly composed of a feature extractor front-end together with a ...
    • 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)
      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 Esfahani, 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 ...
    • Machine and deep learning approaches to localization and range estimation of underwater acoustic sources 

      Houégnigan, Ludwig; Safari, Pooyan; Nadeu Camprubí, Climent; André, Michel; Van der Schaar, Mike Connor Roger Malcolm (Institute of Electrical and Electronics Engineers (IEEE), 2017)
      Conference lecture
      Restricted access - publisher's policy
      This paper introduces ongoing experiments and early results for the underwater localization and range estimation of acoustic sources. Beyond classical results obtained for direction of arrival estimation, results concerning ...
    • Restricted Boltzmann Machine vectors for speaker clustering 

      Khan, Umair; Safari, Pooyan; Hernando Pericás, Francisco Javier (International Speech Communication Association (ISCA), 2018)
      Conference lecture
      Open Access
      Restricted Boltzmann Machines (RBMs) have been used both in the front-end and backend of speaker verification systems. In this work, we apply RBMs as a front-end in the context of speaker clustering. Speakers' utterances ...
    • Restricted Boltzmann machine vectors for speaker clustering and tracking tasks in TV broadcast shows 

      Khan, Umair; Safari, Pooyan; Hernando Pericás, Francisco Javier (Multidisciplinary Digital Publishing Institute, 2019-07-09)
      Article
      Open Access
      Restricted Boltzmann Machines (RBMs) have shown success in both the front-end and backend of speaker verification systems. In this paper, we propose applying RBMs to the front-end for the tasks of speaker clustering and ...
    • Self multi-head attention for speaker recognition 

      India Massana, Miquel Àngel; Safari, Pooyan; Hernando Pericás, Francisco Javier (International Speech Communication Association (ISCA), 2019)
      Conference lecture
      Open Access
      Most state-of-the-art Deep Learning (DL) approaches forspeaker recognition work on a short utterance level. Given thespeech signal, these algorithms extract a sequence of speakerembeddings from short segments and those are ...
    • Self-attention encoding and pooling for speaker recognition 

      Safari, Pooyan; India Massana, Miquel Àngel; Hernando Pericás, Francisco Javier (International Speech Communication Association (ISCA), 2020)
      Conference report
      Open Access
      The computing power of mobile devices limits the end-user applications in terms of storage size, processing, memory and energy consumption. These limitations motivate researchers for the design of more efficient deep models. ...
    • Speaker recognition by means of restricted Boltzmann machine adaptation 

      Safari, Pooyan; Ghahabi Esfahani, 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 ...