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        <datestamp>2025-01-22T04:53:26Z</datestamp>
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          <dc:title>PLSA言語モデル適応におけるアニーリングスケジュールの評価</dc:title>
          <dc:title xml:lang="en">Evaluation of annealing schadule for PLSA language model adaptaion</dc:title>
          <jpcoar:creator>
            <jpcoar:creatorName>加藤正治</jpcoar:creatorName>
            <jpcoar:creatorName>小坂, 哲夫</jpcoar:creatorName>
            <jpcoar:creatorName>伊藤, 彰則</jpcoar:creatorName>
            <jpcoar:creatorName>牧野, 正三</jpcoar:creatorName>
          </jpcoar:creator>
          <jpcoar:creator>
            <jpcoar:creatorName xml:lang="en">Masaharu, Kato</jpcoar:creatorName>
            <jpcoar:creatorName xml:lang="en">Tetsuo, Kosaka</jpcoar:creatorName>
            <jpcoar:creatorName xml:lang="en">Akinori, Ito</jpcoar:creatorName>
            <jpcoar:creatorName xml:lang="en">Shozo, Makino</jpcoar:creatorName>
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          <datacite:description descriptionType="Other">潜在的意味解析 (PLSA) の学習においてアニーリングを行うことは局所最適解に陥ることを防ぐ意味で重要である．本報告では，アニーリングスケジュールを連続関数で定義することで明確化し網羅的な比較検討をする．提案法を 「日本語話し言葉コーパス (CSJ) 」 の講演音声で評価しところ，増加関数に基づくアニーリングスケジュールで作成した言語モデルは， 28.7％ のパープレキシテイ削減と 5.3％ の単語誤り率の改善を得た．</datacite:description>
          <datacite:description descriptionType="Other">Probabilistic Latent Semantic Analysis (PLSA) is a powerful statistical laguage model. However the PLSA has the local maxima problem. To overcame this problem, the EM annealing algorithm has been proposed. In this paper, we designed annealing schedule /3 with some continuous functions. As a result, we found that increas ing functions and square root functions are the best for annealing schedule. In the experiment, we obtain 28.7% perplexity reduction and 5.3% word error rate reduction.</datacite:description>
          <dc:publisher xml:lang="ja">情報処理学会</dc:publisher>
          <datacite:date dateType="Issued">2008-12-02</datacite:date>
          <dc:language>jpn</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/56584</jpcoar:identifier>
          <jpcoar:sourceIdentifier identifierType="NCID">AN10442647</jpcoar:sourceIdentifier>
          <jpcoar:sourceTitle>情報処理学会研究報告音声言語情報処理（SLP）</jpcoar:sourceTitle>
          <jpcoar:volume>2008</jpcoar:volume>
          <jpcoar:issue>123(2008-SLP-074)</jpcoar:issue>
          <jpcoar:pageStart>49</jpcoar:pageStart>
          <jpcoar:pageEnd>53</jpcoar:pageEnd>
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            <datacite:date dateType="Available">2010-12-02</datacite:date>
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