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  <doc>
    <id>2488</id>
    <completedYear/>
    <publishedYear>2020</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst/>
    <pageLast/>
    <pageNumber/>
    <edition/>
    <issue/>
    <volume/>
    <type>conferenceobject</type>
    <publisherName/>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>--</completedDate>
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    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">Text/Language-Independent Unknown Speaker Rejection Method Using LSP Codes</title>
    <abstract language="eng">Scam phone calls pretending relatives have become a major social problem. However, current countermeasure against such scam phone calls stays only enlightenment activities although there is a limited number of technical measures in telephones. In this study, we have proposed a text-independent unknown speaker rejection method which recognizes whether a known speaker or an unknown speaker on receiving a call. In this method, we used a line spectral pair (LSP) spectrogram as the feature and a convolutional neural network (CNN) as the identification engine. From the evaluated results, the proposed method recognized known/unknown speakers with the false acceptance rate (FAR) of 13.1% in Japanese speech and 25.2% in German speech, respectively.</abstract>
    <parentTitle language="eng">IEEE 9th Global Conference on Consumer Electronics (GCCE 2020): 13-16 Oct. 2020, Kobe, Japan</parentTitle>
    <identifier type="doi">10.1109/GCCE50665.2020.9291835</identifier>
    <enrichment key="opus.import.date">2022-01-21T12:31:59+00:00</enrichment>
    <enrichment key="opus.source">sword</enrichment>
    <enrichment key="opus.import.user">importuser</enrichment>
    <enrichment key="BegutachtungStatus">peer-reviewed</enrichment>
    <licence>Keine Lizenz - Es gilt das deutsche Urheberrecht: § 53 UrhG</licence>
    <author>Toru Hiyama</author>
    <author>Armin Sehr</author>
    <author>Takahiro Yoshida</author>
    <author>Seiichiro Hangai</author>
    <collection role="institutes" number="FakEI">Fakultät Elektro- und Informationstechnik</collection>
    <collection role="othforschungsschwerpunkt" number="16317">Sensorik</collection>
    <collection role="institutes" number="">Labor Elektroakustik</collection>
  </doc>
</export-example>
