{"updated":"2025-01-21T14:45:55.298405+00:00","metadata":{"_oai":{"id":"oai:ipsj.ixsq.nii.ac.jp:00092749","sets":["934:1022:7036:7206"]},"path":["7206"],"owner":"11","recid":"92749","title":["視聴者の時刻同期コメントを用いた楽曲動画の印象分類"],"pubdate":{"attribute_name":"公開日","attribute_value":"2013-06-28"},"_buckets":{"deposit":"e6dce224-f5e3-475e-9c78-c2c767cdf2ba"},"_deposit":{"id":"92749","pid":{"type":"depid","value":"92749","revision_id":0},"owners":[11],"status":"published","created_by":11},"item_title":"視聴者の時刻同期コメントを用いた楽曲動画の印象分類","author_link":["0","0"],"item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"視聴者の時刻同期コメントを用いた楽曲動画の印象分類"},{"subitem_title":"Using Viewers' Time-synchronized Comments for Mood Classification of Music Video Clips","subitem_title_language":"en"}]},"item_keyword":{"attribute_name":"キーワード","attribute_value_mlt":[{"subitem_subject":"[研究論文] 印象推定，ユーザ生成メディア，音楽情報検索","subitem_subject_scheme":"Other"}]},"item_type_id":"3","publish_date":"2013-06-28","item_3_text_3":{"attribute_name":"著者所属","attribute_value_mlt":[{"subitem_text_value":"京都大学大学院情報学研究科"},{"subitem_text_value":"明治大学総合数理学部／科学技術振興機構CREST"}]},"item_3_text_4":{"attribute_name":"著者所属(英)","attribute_value_mlt":[{"subitem_text_value":"Graduate School of Informatics, Kyoto University","subitem_text_language":"en"},{"subitem_text_value":"School of Interdisciplinary Mathematical Sciences, Meiji University / JST CREST","subitem_text_language":"en"}]},"item_language":{"attribute_name":"言語","attribute_value_mlt":[{"subitem_language":"jpn"}]},"item_publisher":{"attribute_name":"出版者","attribute_value_mlt":[{"subitem_publisher":"情報処理学会","subitem_publisher_language":"ja"}]},"publish_status":"0","weko_shared_id":-1,"item_file_price":{"attribute_name":"Billing file","attribute_type":"file","attribute_value_mlt":[{"url":{"url":"https://ipsj.ixsq.nii.ac.jp/record/92749/files/IPSJ-TOD0603007.pdf"},"date":[{"dateType":"Available","dateValue":"2015-06-28"}],"format":"application/pdf","billing":["billing_file"],"filename":"IPSJ-TOD0603007.pdf","filesize":[{"value":"729.2 kB"}],"mimetype":"application/pdf","priceinfo":[{"tax":["include_tax"],"price":"660","billingrole":"5"},{"tax":["include_tax"],"price":"330","billingrole":"6"},{"tax":["include_tax"],"price":"0","billingrole":"13"},{"tax":["include_tax"],"price":"0","billingrole":"39"},{"tax":["include_tax"],"price":"0","billingrole":"44"}],"accessrole":"open_date","version_id":"31d59cb3-8191-4be2-9bc2-0f11a142822b","displaytype":"detail","licensetype":"license_note","license_note":"Copyright (c) 2013 by the Information Processing Society of Japan"}]},"item_3_creator_5":{"attribute_name":"著者名","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"山本, 岳洋"},{"creatorName":"中村, 聡史"}],"nameIdentifiers":[{}]}]},"item_3_creator_6":{"attribute_name":"著者名(英)","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"Takehiro, Yamamoto","creatorNameLang":"en"},{"creatorName":"Satoshi, Nakamura","creatorNameLang":"en"}],"nameIdentifiers":[{}]}]},"item_3_source_id_9":{"attribute_name":"書誌レコードID","attribute_value_mlt":[{"subitem_source_identifier":"AA11464847","subitem_source_identifier_type":"NCID"}]},"item_resource_type":{"attribute_name":"資源タイプ","attribute_value_mlt":[{"resourceuri":"http://purl.org/coar/resource_type/c_6501","resourcetype":"journal article"}]},"item_3_source_id_11":{"attribute_name":"ISSN","attribute_value_mlt":[{"subitem_source_identifier":"1882-7799","subitem_source_identifier_type":"ISSN"}]},"item_3_description_7":{"attribute_name":"論文抄録","attribute_value_mlt":[{"subitem_description":"本稿では，印象に基づく楽曲検索実現のために，動画共有サイト上に投稿された楽曲動画を，可愛らしい，切ない，元気がでるといった印象に分類する手法を提案する．楽曲動画の印象分類のため，ユーザの投稿した時刻同期コメントに着目し，単語の品詞，文字の繰返し構造，楽曲のサビ区間の3つを利用する．実験では1,314本の楽曲動画を7印象クラスに分類し，提案手法がF値のマクロ平均で0.659を達成しベースライン手法よりも高い精度を得た．また，楽曲の歌詞や音響特徴量を用いた分類手法とも比較し，提案手法の有効性を示した．","subitem_description_type":"Other"}]},"item_3_description_8":{"attribute_name":"論文抄録(英)","attribute_value_mlt":[{"subitem_description":"This paper proposes a method to classify music video clips, which are uploaded to the video sharing service, into the mood categories such as “cute,” “sorrow” and “cheerful.” The method leverages viewers' time-synchronized comments posted to video clips to classify the video clips into moods. It extracts features from the comments in the terms of (1) parts-of-speech, (2) lengthened words and (3) chorus parts of the music. Our experimental results showed that out method achieved the best classification performance (Macro F-measure of 0.659) compared with some baselines. In addition, our method outperformed the conventional approaches that utilize lyrics and audio features of musics.","subitem_description_type":"Other"}]},"item_3_biblio_info_10":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicPageEnd":"72","bibliographic_titles":[{"bibliographic_title":"情報処理学会論文誌データベース（TOD）"}],"bibliographicPageStart":"61","bibliographicIssueDates":{"bibliographicIssueDate":"2013-06-28","bibliographicIssueDateType":"Issued"},"bibliographicIssueNumber":"3","bibliographicVolumeNumber":"6"}]},"relation_version_is_last":true,"weko_creator_id":"11"},"created":"2025-01-18T23:41:32.960383+00:00","id":92749,"links":{}}