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4 research outcomes, page 1 of 1
  • publication . Preprint . Conference object . Contribution for newspaper or weekly magazine . 2018
    Open Access English
    Authors:
    Ahmed Ali; Stephan Vogel; Steve Renals;
    Project: EC | SUMMA (688139)

    This paper describes the Arabic MGB-3 Challenge - Arabic Speech Recognition in the Wild. Unlike last year's Arabic MGB-2 Challenge, for which the recognition task was based on more than 1,200 hours broadcast TV news recordings from Aljazeera Arabic TV programs, MGB-3 em...

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  • publication . Article . Conference object . Other literature type . 2017
    Open Access
    Authors:
    Renars Liepins; Ulrich Germann; Guntis Barzdins; Alexandra Birch; Steve Renals; Susanne Weber; Peggy van der Kreeft; Hervé Bourlard; João Prieto; Ondrej Klejch; ...
    Publisher: Zenodo
    Project: EC | SUMMA (688139)

    We present the first prototype of the SUMMA Platform: an integrated platform for multilingual media monitoring. The platform contains a rich suite of low-level and high-level natural language processing technologies: automatic speech recognition of broadcast media, mach...

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  • publication . Preprint . Conference object . Contribution for newspaper or weekly magazine . 2016
    Open Access English
    Authors:
    Ahmed Ali; Peter Bell; James Glass; Yacine Messaoui; Hamdy Mubarak; Steve Renals; Yifan Zhang;
    Project: EC | SUMMA (688139)

    This paper describes the Arabic Multi-Genre Broadcast (MGB-2) Challenge for SLT-2016. Unlike last year’s English MGB Challenge, which focused on recognition of diverse TV genres, this year, the challenge has an emphasis on handling the diversity in dialect in Arabic spe...

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  • publication . Conference object . Preprint . Contribution for newspaper or weekly magazine . 2016
    Open Access English
    Authors:
    Ahmed Ali; Najim Dehak; Patrick Cardinal; Sameer Khurana; Sree Harsha Yella; James Glass; Peter Bell; Steve Renals;
    Publisher: ISCA
    Project: EC | SUMMA (688139)

    In this paper, we investigate different approaches for dialect identification in Arabic broadcast speech. These methods are based on phonetic and lexical features obtained from a speech recognition system, and bottleneck features using the <br/>i-vector framework. We st...

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4 research outcomes, page 1 of 1