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        <datestamp>2025-01-19T18:24:05Z</datestamp>
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        <jpcoar:jpcoar xmlns:datacite="https://schema.datacite.org/meta/kernel-4/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:dcndl="http://ndl.go.jp/dcndl/terms/" xmlns:dcterms="http://purl.org/dc/terms/" xmlns:jpcoar="https://github.com/JPCOAR/schema/blob/master/1.0/" xmlns:oaire="http://namespace.openaire.eu/schema/oaire/" xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#" xmlns:rioxxterms="http://www.rioxx.net/schema/v2.0/rioxxterms/" xmlns:xs="http://www.w3.org/2001/XMLSchema" xmlns="https://github.com/JPCOAR/schema/blob/master/1.0/" xsi:schemaLocation="https://github.com/JPCOAR/schema/blob/master/1.0/jpcoar_scm.xsd">
          <dc:title>クラウドソーシングと防音室における音声了解度実験の対比</dc:title>
          <dc:title xml:lang="en">Comparison of speech intelligibility results between laboratory and crowd-sourcing experiments</dc:title>
          <jpcoar:creator>
            <jpcoar:creatorName>山本, 絢子</jpcoar:creatorName>
          </jpcoar:creator>
          <jpcoar:creator>
            <jpcoar:creatorName>入野, 俊夫</jpcoar:creatorName>
          </jpcoar:creator>
          <jpcoar:creator>
            <jpcoar:creatorName>新井, 賢一</jpcoar:creatorName>
          </jpcoar:creator>
          <jpcoar:creator>
            <jpcoar:creatorName>荒木, 章子</jpcoar:creatorName>
          </jpcoar:creator>
          <jpcoar:creator>
            <jpcoar:creatorName>小川, 厚徳</jpcoar:creatorName>
          </jpcoar:creator>
          <jpcoar:creator>
            <jpcoar:creatorName>木下, 慶介</jpcoar:creatorName>
          </jpcoar:creator>
          <jpcoar:creator>
            <jpcoar:creatorName>中谷, 智広</jpcoar:creatorName>
          </jpcoar:creator>
          <jpcoar:creator>
            <jpcoar:creatorName xml:lang="en">Ayako, Yamamoto</jpcoar:creatorName>
          </jpcoar:creator>
          <jpcoar:creator>
            <jpcoar:creatorName xml:lang="en">Toshio, Irino</jpcoar:creatorName>
          </jpcoar:creator>
          <jpcoar:creator>
            <jpcoar:creatorName xml:lang="en">Kenichi, Arai</jpcoar:creatorName>
          </jpcoar:creator>
          <jpcoar:creator>
            <jpcoar:creatorName xml:lang="en">Shoko, Araki</jpcoar:creatorName>
          </jpcoar:creator>
          <jpcoar:creator>
            <jpcoar:creatorName xml:lang="en">Atsunori, Ogawa</jpcoar:creatorName>
          </jpcoar:creator>
          <jpcoar:creator>
            <jpcoar:creatorName xml:lang="en">Keisuke, Kinoshita</jpcoar:creatorName>
          </jpcoar:creator>
          <jpcoar:creator>
            <jpcoar:creatorName xml:lang="en">Tomohiro, Nakatani</jpcoar:creatorName>
          </jpcoar:creator>
          <jpcoar:subject subjectScheme="Other">ポスターセッション</jpcoar:subject>
          <datacite:description descriptionType="Other">今まで音声了解度の客観評価指標を開発することを目的として、数多くの主観評価実験が行われてきた。しかし、コロナ禍により密閉した防音室で実験を行うことが非常に困難となった。遠隔実験に頼ったデータ収集を行わざるを得ないが、聴取条件の統制ができないため収集したデータの信頼性が明確でない。そこで、本研究ではクラウドソーシングを利用した遠隔実験と防音室で行われた実験による音声了解度を対比した。遠隔実験のほうが語音聴 取閾値 (SRT) が若干高く、標準偏差も大きかった。しかし、音声強調処理条件間でのSRTの大小関係は防音室実験 と同じ傾向を示し、客観評価指標の開発に利用可能であることが示唆された。さらに、練習問題の成績でデータの選 別をしたところ、遠隔実験と防音室実験の結果を若干近づけることができた。実験参加者のプロフィールから一般化  線型モデルによってSRT値をステップワイズ近似した際にも、練習問題の成績が唯一相関があるものとして抽出された。さらなる要因の追求は必要だが、データ選別の一つの目安となると考える。</datacite:description>
          <datacite:description descriptionType="Other">Many subjective experiments have been performed to develop objective speech intelligibility measure.But COVID-19 has made it extremely difficult to conduct experiments in a laboratory. One of solutions is to perform remote testing by using crowd sourcing. It is not, however, clear whether the results are entirely reliable because we cannot control their listening conditions. In this study, we compared speech intelligibility results obtained by remote testing and two laboratory experiments. The results showed that the average and the standard deviation of speech reception threshold (SRT) of the remote testing were greater than those of the laboratory experiments. But the variation of the SRTs across the speech enhancement conditions were very similar between them. It implies that results of remote testing may be usable to develop the objective measure as well as those of laboratory experiments. We also show data reduction based on the practice score slightly improves the SRT values. The SRT prediction using the stepwise approximation with the generalized linear model extracted the practice score as solely correlated explanatory variable. It seems a good criterion for data selection although other factors should be investigated more.</datacite:description>
          <dc:publisher xml:lang="ja">情報処理学会</dc:publisher>
          <datacite:date dateType="Issued">2021-02-24</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/209755</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>2021-SLP-136</jpcoar:volume>
          <jpcoar:issue>17</jpcoar:issue>
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          <jpcoar:pageEnd>6</jpcoar:pageEnd>
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