November 2, 2019 Conference paper Open Access

Potapczyk, Tomasz; Przybysz, Pawel; Chochowski, Marcin; Szumaczuk, Artur

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  <identifier identifierType="DOI">10.5281/zenodo.3525498</identifier>
  <creators>
    <creator>
      <creatorName>Potapczyk, Tomasz</creatorName>
      <givenName>Tomasz</givenName>
      <familyName>Potapczyk</familyName>
      <affiliation>Samsung R&amp;D Institute, Poland</affiliation>
    </creator>
    <creator>
      <creatorName>Przybysz, Pawel</creatorName>
      <givenName>Pawel</givenName>
      <familyName>Przybysz</familyName>
      <affiliation>Samsung R&amp;D Institute, Poland</affiliation>
    </creator>
    <creator>
      <creatorName>Chochowski, Marcin</creatorName>
      <givenName>Marcin</givenName>
      <familyName>Chochowski</familyName>
      <affiliation>Samsung R&amp;D Institute, Poland</affiliation>
    </creator>
    <creator>
      <creatorName>Szumaczuk, Artur</creatorName>
      <givenName>Artur</givenName>
      <familyName>Szumaczuk</familyName>
      <affiliation>Samsung R&amp;D Institute, Poland</affiliation>
    </creator>
  </creators>
  <titles>
    <title>Samsung's System for the IWSLT 2019 End-to-End Speech Translation Task</title>
  </titles>
  <publisher>Zenodo</publisher>
  <publicationYear>2019</publicationYear>
  <dates>
    <date dateType="Issued">2019-11-02</date>
  </dates>
  <language>en</language>
  <resourceType resourceTypeGeneral="Text">Conference paper</resourceType>
  <alternateIdentifiers>
    <alternateIdentifier alternateIdentifierType="url">https://zenodo.org/record/3525498</alternateIdentifier>
  </alternateIdentifiers>
  <relatedIdentifiers>
    <relatedIdentifier relatedIdentifierType="DOI" relationType="IsVersionOf">10.5281/zenodo.3525497</relatedIdentifier>
    <relatedIdentifier relatedIdentifierType="URL" relationType="IsPartOf">https://zenodo.org/communities/iwslt2019</relatedIdentifier>
  </relatedIdentifiers>
  <rightsList>
    <rights rightsURI="https://creativecommons.org/licenses/by/4.0/legalcode">Creative Commons Attribution 4.0 International</rights>
    <rights rightsURI="info:eu-repo/semantics/openAccess">Open Access</rights>
  </rightsList>
  <descriptions>
    <description descriptionType="Abstract">&lt;p&gt;This paper describes the submission to IWSLT 2019 End- to-End speech translation task by Samsung R&amp;amp;D Institute, Poland. We decided to focus on end-to-end English to German TED lectures translation and did not provide any submission for other speech tasks. We used a slightly altered Transformer&amp;nbsp;architecture with standard convolutional layer preparing the audio input to Transformer en- coder. Additionally, we propose an audio segmentation al- gorithm maximizing BLEU score on tst2015 test set.&lt;/p&gt;</description>
  </descriptions>
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