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      <title-group>
        <article-title>Preface to the First Workshop on Current Trends in Text Simplification</article-title>
      </title-group>
      <contrib-group>
        <contrib contrib-type="author">
          <string-name>Horacio Saggion</string-name>
          <xref ref-type="aff" rid="aff0">0</xref>
        </contrib>
        <contrib contrib-type="author">
          <string-name>Sanja Štajner</string-name>
          <xref ref-type="aff" rid="aff1">1</xref>
        </contrib>
        <contrib contrib-type="author">
          <string-name>Daniel Ferrés</string-name>
          <xref ref-type="aff" rid="aff0">0</xref>
        </contrib>
        <contrib contrib-type="author">
          <string-name>Kim Cheng Sheang</string-name>
          <xref ref-type="aff" rid="aff0">0</xref>
        </contrib>
        <aff id="aff0">
          <label>0</label>
          <institution>LaSTUS/TALN, Department of Information and Communication Technologies, Universitat Pompeu Fabra</institution>
          ,
          <country country="ES">Spain</country>
        </aff>
        <aff id="aff1">
          <label>1</label>
          <institution>Symanto Research</institution>
          ,
          <country country="DE">Germany</country>
        </aff>
      </contrib-group>
      <abstract>
        <p>Thanks to the availability of texts on the Web in recent years, increased knowledge and information have been made available to broader audiences. However, the way in which a text is written-vocabulary, syntax, text organisation/structure-can be dificult to read and understand for many people, especially those with low literacy, cognitive or linguistic impairment, or those with limited knowledge of the language of the text. Texts containing uncommon words or long and complicated sentences can be dificult to read and understand by people as well as dificult to analyse by machines. Automatic text simplification is the process of transforming a text into another text which, ideally conveying the same message, will be easier to read and understand by a broader audience.</p>
      </abstract>
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    <sec id="sec-1">
      <title>-</title>
      <p>We are grateful to Aline Villavicencio (University of Shefield, UK) and Matt Huenerfauth
(Rochester Institute of Technology, USA) for accepting to give invited talks.</p>
      <p>We express our gratitude to the members of the program committee for their detailed reviews
and support.</p>
      <p>We acknowledge support from the project Context-aware Multilingual Text Simplification
(ConMuTeS) PID2019-109066GB-I00/AEI/10.13039/501100011033 awarded by Ministerio de
Ciencia, Innovación y Universidades (MCIU) and by Agencia Estatal de Investigación (AEI) of
Spain.</p>
    </sec>
    <sec id="sec-2">
      <title>Workshop Organizers</title>
      <sec id="sec-2-1">
        <title>Chairs</title>
        <p>Horacio Saggion (Universitat Pompeu Fabra, Spain)
Sanja Štajner (Symanto Research, Germany)
Daniel Ferrés (Universitat Pompeu Fabra, Spain)</p>
      </sec>
      <sec id="sec-2-2">
        <title>Proceedings</title>
        <p>Kim Cheng Sheang (Universitat Pompeu Fabra, Spain)</p>
      </sec>
    </sec>
    <sec id="sec-3">
      <title>Program Committee</title>
      <p>David Kauchak (Pomona College, USA)
Elena Lloret (Universidad de Alicante, Spain)
Louis Martin (Facebook, UK)
Lourdes Moreno López (Universidad Carlos III, Spain)
Gustavo Henrique Paetzold (Universidade Tecnológica Federal do Paraná, Brazil)
Benoît Sagot (INRIA, France)
Carolina Scarton (University of Shefield, UK)
Matthew Shardlow (Manchester Metropolitan University, UK)
Advaith Siddharthan (The Open University, UK)
Lucia Specia (Imperial College, UK)
Giulia Venturi (Istituto di Linguistica Computazionale “Antonio Zampolli”, Italy)
Victoria Yaneva (National Board of Medical Examiners, USA)</p>
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