Joe Simon

Results: 42



#Item
1

VICTO cd 116 JOE MORRIS / SIMON H FELL / ALEX WARD The Necessary and the Possible

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Source URL: www.victo.qc.ca

Language: English - Date: 2010-12-09 10:57:48
    2

    A Hybrid ANN/DBN Approach to Articulatory Feature Recognition Joe Frankel∗, Simon King† Centre for Speech Technology Research The University of Edinburgh

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    Source URL: www.cstr.ed.ac.uk

    Language: English - Date: 2005-07-04 11:07:03
      3

      Typeset by REVTEX 4 for JASA(A,Y) Speech production knowledge in automatic speech recognition Simon Kinga) and Joe Frankel Centre for Speech Technology Research, 2

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      Source URL: ttic.uchicago.edu

      Language: English - Date: 2012-12-17 06:04:18
        4

        MONOLINGUAL AND CROSSLINGUAL COMPARISON OF TANDEM FEATURES DERIVED FROM ARTICULATORY AND PHONE MLPS ¨ ur C¸etin1 Mathew Magimai-Doss2 Karen Livescu3 Ozg¨ Arthur Kantor4 Simon King5 Chris Bartels6 Joe Frankel5 1

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        Source URL: www.cstr.ed.ac.uk

        Language: English - Date: 2007-10-08 06:01:18
          5

          POSTERIOR-BASED CONFIDENCE MEASURES FOR SPOKEN TERM DETECTION Dong Wang1 , Javier Tejedor1,2 , Joe Frankel1 , Simon King1 and Jose Col´as2 1. The Centre for Speech Technology Research, University of Edinburgh, UK 2. Hum

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          Source URL: www.cstr.ed.ac.uk

          Language: English - Date: 2009-09-29 11:32:57
            6

            STOCHASTIC PRONUNCIATION MODELLING AND SOFT MATCH FOR OUT-OF-VOCABULARY SPOKEN TERM DETECTION Dong Wang, Simon King, Joe Frankel, Peter Bell The Centre for Speech Technology Research, University of Edinburgh, UK ABSTRACT

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            Source URL: www.cstr.ed.ac.uk

            Language: English - Date: 2010-11-09 07:41:22
              7

              Growing bottleneck features for tandem ASR Joe Frankel, Dong Wang, Simon King Centre for Speech Technology Research, University of Edinburgh, UK ; ; Abstract

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              Source URL: www.cstr.ed.ac.uk

              Language: English - Date: 2009-04-09 05:49:37
                8

                Articulatory Feature Classifiers Trained on 2000 hours of Telephone Speech ¨ ur C¸etin2 . Joe Frankel1,2 , Mathew Magimai-Doss2 , Simon King1 , Karen Livescu3 , Ozg¨ 1 University of Edinburgh, 2 ICSI, 3 MIT

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                Source URL: ttic.uchicago.edu

                Language: English - Date: 2008-02-21 07:48:12
                  9

                  JOURNAL 1 Speech Recognition using Linear Dynamic Models Joe Frankel, Member, IEEE and Simon King, Member, IEEE

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                  Source URL: www.cstr.ed.ac.uk

                  Language: English - Date: 2006-05-09 04:46:45
                    10

                    Stochastic Pronunciation Modelling for Spoken Term Detection Dong Wang, Simon King, Joe Frankel The Centre for Speech Technology Research, University of Edinburgh, UK , ,

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                    Source URL: www.cstr.ed.ac.uk

                    Language: English - Date: 2009-09-29 11:32:57
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