1 Ocak 2005 Konferans bildirisi Açık Erişim

Palaz, H; Kanak, A; Bicil, Y; Dogan, MU

DataCite XML

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  <identifier identifierType="URL">https://aperta.ulakbim.gov.tr/record/95711</identifier>
  <creators>
    <creator>
      <creatorName>Palaz, H</creatorName>
      <givenName>H</givenName>
      <familyName>Palaz</familyName>
    </creator>
    <creator>
      <creatorName>Kanak, A</creatorName>
      <givenName>A</givenName>
      <familyName>Kanak</familyName>
    </creator>
    <creator>
      <creatorName>Bicil, Y</creatorName>
      <givenName>Y</givenName>
      <familyName>Bicil</familyName>
    </creator>
    <creator>
      <creatorName>Dogan, MU</creatorName>
      <givenName>MU</givenName>
      <familyName>Dogan</familyName>
    </creator>
  </creators>
  <titles>
    <title>Tren-Turkish Recognition Engine For Distributed Applications</title>
  </titles>
  <publisher>Aperta</publisher>
  <publicationYear>2005</publicationYear>
  <dates>
    <date dateType="Issued">2005-01-01</date>
  </dates>
  <resourceType resourceTypeGeneral="Text">Conference paper</resourceType>
  <alternateIdentifiers>
    <alternateIdentifier alternateIdentifierType="url">https://aperta.ulakbim.gov.tr/record/95711</alternateIdentifier>
  </alternateIdentifiers>
  <relatedIdentifiers>
    <relatedIdentifier relatedIdentifierType="DOI" relationType="IsVersionOf">10.81043/aperta.95710</relatedIdentifier>
    <relatedIdentifier relatedIdentifierType="DOI" relationType="IsIdenticalTo">10.81043/aperta.95711</relatedIdentifier>
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  <rightsList>
    <rights rightsURI="http://www.opendefinition.org/licenses/cc-by">Creative Commons Attribution</rights>
    <rights rightsURI="info:eu-repo/semantics/openAccess">Open Access</rights>
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  <descriptions>
    <description descriptionType="Abstract">Turkish Recognition ENgine (TREN) is a modular, Hidden Markov Model based (HMM-based), speaker independent and Distributed Component Object Model based (DCOM-based) speech recognition system. TREN is a two-layered system containing specialized modules that allow a fully interoperable platform including a Turkish speech recognizer, a feature extractor, an end-point detector and a performance monitoring module. in order to increase the recognition performance, a Turkish telephony speech database with a very large word corpus is collected and statistically the widest span of triphones representing Turkish is examined. TREN has been used to assist speech technologies which require a modular and a multithreaded speech recognizer with dynamic load sharing facilities.</description>
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