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Study of Parallelization of the Training for Automatic Speech Recognition

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High Performance Computing and Networking (HPCN-Europe 2000)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 1823))

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Abstract

In this work we study the parallelization of the training phase for an automatic speech recognition system using the Hidden Markov Models. The vocabulary is uniformly distributed on processors, but the Markovian network of the treated application is duplicated on all processors. The proposed parallel algorithms are based on two strategies of communications. In the first one, called regrouping algorithm, communications are delayed until the training of all local sentences is finished. In the second one, called cutting algorithm, packages of optimal sizes is firstly determined and then asynchronous communications are performed after the training of each package. Experimental results show that good performances can be obtained with the second algorithm.

Supported by the European Program INCO-DC, “DAPPI” Project

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References

  1. E.M. Daoudi, A. Meziane, Y.O. MOhamed El Hadj, “Parallel HMM Model for Automatic Speech recognition”, RR-Lari, Oujda, 1999, Submitted for publication.

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Author information

Authors and Affiliations

  1. Faculté des Sciences, Départ. Maths — Informatique, LaRI, Université Mohammed Ier, 60 000, Oujda, Morocco

    Mostafa El Daoudi, Abdelouafi Meziane & Yahya Ould Mohamed El Hadj

Authors
  1. Mostafa El Daoudi
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  2. Abdelouafi Meziane
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  3. Yahya Ould Mohamed El Hadj
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Editor information

Editors and Affiliations

  1. Institute of Computer Science and Academic Computer Center CYFRONET, University of Mining and Metallurgy (AGH), al. Mickiewicza 30, 30-059, Cracow, Poland

    Marian Bubak

  2. Faculteit der Natuurwetenschappen, Wiskunde en Informatica, Universiteit van Amsterdam, 1098 SJ, Amsterdam, The Netherlands

    Hamideh Afsarmanesh  & Bob Hertzberger  & 

  3. California Institute of Technology, Caltech 158-79, Pasadena, CA, 91125, USA

    Roy Williams

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© 2000 Springer-Verlag Berlin Heidelberg

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El Daoudi, M., Meziane, A., El Hadj, Y.O.M. (2000). Study of Parallelization of the Training for Automatic Speech Recognition. In: Bubak, M., Afsarmanesh, H., Hertzberger, B., Williams, R. (eds) High Performance Computing and Networking. HPCN-Europe 2000. Lecture Notes in Computer Science, vol 1823. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45492-6_66

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  • DOI: https://doi.org/10.1007/3-540-45492-6_66

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-67553-2

  • Online ISBN: 978-3-540-45492-2

  • eBook Packages: Springer Book Archive

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