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          <dc:title>A comparative study on modeling and controlling emotional acoustic parameters in neural networks based Japanese and Spanish speech synthesis</dc:title>
          <dc:title xml:lang="en">A comparative study on modeling and controlling emotional acoustic parameters in neural networks based Japanese and Spanish speech synthesis</dc:title>
          <jpcoar:creator>
            <jpcoar:creatorName>Jaime, Lorenzo-Trueba</jpcoar:creatorName>
          </jpcoar:creator>
          <jpcoar:creator>
            <jpcoar:creatorName>Shinji, Takaki</jpcoar:creatorName>
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          <jpcoar:creator>
            <jpcoar:creatorName>Junichi, Yamagishi</jpcoar:creatorName>
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          <jpcoar:creator>
            <jpcoar:creatorName xml:lang="en">Jaime, Lorenzo-Trueba</jpcoar:creatorName>
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          <jpcoar:creator>
            <jpcoar:creatorName xml:lang="en">Shinji, Takaki</jpcoar:creatorName>
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          <jpcoar:creator>
            <jpcoar:creatorName xml:lang="en">Junichi, Yamagishi</jpcoar:creatorName>
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          <jpcoar:subject subjectScheme="Other">音声合成</jpcoar:subject>
          <datacite:description descriptionType="Other">In neural network based speech synthesis, adding a one-hot vector to the input is an easy, intuitive but useful way to model multiple speakers or multiple language. In this paper, we use the one-hot vector for modeling and controlling emotional acoustic parameters. We have used Spanish and Japanese databases having the multiple acted emotional speech uttered by professional speakers in our experiment and will show the performance of the one-hot vector approach.</datacite:description>
          <datacite:description descriptionType="Other">In neural network based speech synthesis, adding a one-hot vector to the input is an easy, intuitive but useful way to model multiple speakers or multiple language. In this paper, we use the one-hot vector for modeling and controlling emotional acoustic parameters. We have used Spanish and Japanese databases having the multiple acted emotional speech uttered by professional speakers in our experiment and will show the performance of the one-hot vector approach.</datacite:description>
          <dc:publisher xml:lang="ja">情報処理学会</dc:publisher>
          <datacite:date dateType="Issued">2016-12-13</datacite:date>
          <dc:language>eng</dc:language>
          <dc:type rdf:resource="http://purl.org/coar/resource_type/c_18gh">technical report</dc:type>
          <jpcoar:identifier identifierType="URI">https://ipsj.ixsq.nii.ac.jp/records/176408</jpcoar:identifier>
          <jpcoar:sourceIdentifier identifierType="ISSN">2188-8663</jpcoar:sourceIdentifier>
          <jpcoar:sourceIdentifier identifierType="NCID">AN10442647</jpcoar:sourceIdentifier>
          <jpcoar:sourceTitle>研究報告音声言語情報処理（SLP）</jpcoar:sourceTitle>
          <jpcoar:volume>2016-SLP-114</jpcoar:volume>
          <jpcoar:issue>22</jpcoar:issue>
          <jpcoar:pageStart>1</jpcoar:pageStart>
          <jpcoar:pageEnd>6</jpcoar:pageEnd>
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            <datacite:date dateType="Available">2018-12-13</datacite:date>
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