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        <datestamp>2025-01-19T09:44:09Z</datestamp>
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          <dc:title>An experimental study of accent embedding for text to accented speech synthesis</dc:title>
          <dc:title xml:lang="en">An experimental study of accent embedding for text to accented speech synthesis</dc:title>
          <jpcoar:creator>
            <jpcoar:creatorName>Hewei, Zhang</jpcoar:creatorName>
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          <jpcoar:creator>
            <jpcoar:creatorName>Daisuke, Saito</jpcoar:creatorName>
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            <jpcoar:creatorName>Nobuaki, Minematsu</jpcoar:creatorName>
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          <jpcoar:creator>
            <jpcoar:creatorName xml:lang="en">Hewei, Zhang</jpcoar:creatorName>
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          <jpcoar:creator>
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          <jpcoar:creator>
            <jpcoar:creatorName xml:lang="en">Nobuaki, Minematsu</jpcoar:creatorName>
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          <jpcoar:subject subjectScheme="Other">ポスターセッション2</jpcoar:subject>
          <datacite:description descriptionType="Other">In Text-to-Speech (TTS), End-to-End models had been introduced, which takes text as input and audio as output. This makes it hard to unsupervised control the style, especially accent, which consists of many kinds of acoustic features. We proposed a Phonetic Posterior-Gram-based unsupervised Accent Embedding Extraction model. Experiments showed the ability, robustness to different accent level of training dataset and deeper potential of the model to extract accent features from given utterance.</datacite:description>
          <datacite:description descriptionType="Other">In Text-to-Speech (TTS), End-to-End models had been introduced, which takes text as input and audio as output. This makes it hard to unsupervised control the style, especially accent, which consists of many kinds of acoustic features. We proposed a Phonetic Posterior-Gram-based unsupervised Accent Embedding Extraction model. Experiments showed the ability, robustness to different accent level of training dataset and deeper potential of the model to extract accent features from given utterance.</datacite:description>
          <dc:publisher xml:lang="ja">情報処理学会</dc:publisher>
          <datacite:date dateType="Issued">2024-06-07</datacite:date>
          <dc:language>eng</dc:language>
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          <jpcoar:sourceIdentifier identifierType="NCID">AN10438388</jpcoar:sourceIdentifier>
          <jpcoar:sourceTitle>研究報告音楽情報科学（MUS）</jpcoar:sourceTitle>
          <jpcoar:volume>2024-MUS-140</jpcoar:volume>
          <jpcoar:issue>45</jpcoar:issue>
          <jpcoar:pageStart>1</jpcoar:pageStart>
          <jpcoar:pageEnd>5</jpcoar:pageEnd>
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