{"updated":"2025-01-19T17:35:01.397886+00:00","metadata":{"_oai":{"id":"oai:ipsj.ixsq.nii.ac.jp:00212160","sets":["1164:2735:10526:10644"]},"path":["10644"],"owner":"44499","recid":"212160","title":["NARU: Sign Algorithmの自然勾配法に基づくロスレス音声コーデック"],"pubdate":{"attribute_name":"公開日","attribute_value":"2021-07-20"},"_buckets":{"deposit":"7d3393bd-e7d7-4eec-bd3b-ba4637d5d4a9"},"_deposit":{"id":"212160","pid":{"type":"depid","value":"212160","revision_id":0},"owners":[44499],"status":"published","created_by":44499},"item_title":"NARU: Sign Algorithmの自然勾配法に基づくロスレス音声コーデック","author_link":["540619","540617","540620","540618"],"item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"NARU: Sign Algorithmの自然勾配法に基づくロスレス音声コーデック"},{"subitem_title":"NARU: Natural-gradient AutoRegressive Unlossy Audio Compressor","subitem_title_language":"en"}]},"item_type_id":"4","publish_date":"2021-07-20","item_4_text_3":{"attribute_name":"著者所属","attribute_value_mlt":[{"subitem_text_value":"電気通信大学"},{"subitem_text_value":"電気通信大学"}]},"item_4_text_4":{"attribute_name":"著者所属(英)","attribute_value_mlt":[{"subitem_text_value":"The University of Electro-Communications","subitem_text_language":"en"},{"subitem_text_value":"The University of Electro-Communications","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/212160/files/IPSJ-MPS21134001.pdf","label":"IPSJ-MPS21134001.pdf"},"date":[{"dateType":"Available","dateValue":"2023-07-20"}],"format":"application/pdf","billing":["billing_file"],"filename":"IPSJ-MPS21134001.pdf","filesize":[{"value":"931.9 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":"17"},{"tax":["include_tax"],"price":"0","billingrole":"44"}],"accessrole":"open_date","version_id":"061c3093-61a5-4128-97e1-5f1030252c42","displaytype":"detail","licensetype":"license_note","license_note":"Copyright (c) 2021 by the Information Processing Society of Japan"}]},"item_4_creator_5":{"attribute_name":"著者名","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"峰尾, 太陽"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"庄野, 逸"}],"nameIdentifiers":[{}]}]},"item_4_creator_6":{"attribute_name":"著者名(英)","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"Taiyo, Mineo","creatorNameLang":"en"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"Hayaru, Shouno","creatorNameLang":"en"}],"nameIdentifiers":[{}]}]},"item_4_source_id_9":{"attribute_name":"書誌レコードID","attribute_value_mlt":[{"subitem_source_identifier":"AN10505667","subitem_source_identifier_type":"NCID"}]},"item_4_textarea_12":{"attribute_name":"Notice","attribute_value_mlt":[{"subitem_textarea_value":"SIG Technical Reports are nonrefereed and hence may later appear in any journals, conferences, symposia, etc."}]},"item_resource_type":{"attribute_name":"資源タイプ","attribute_value_mlt":[{"resourceuri":"http://purl.org/coar/resource_type/c_18gh","resourcetype":"technical report"}]},"item_4_source_id_11":{"attribute_name":"ISSN","attribute_value_mlt":[{"subitem_source_identifier":"2188-8833","subitem_source_identifier_type":"ISSN"}]},"item_4_description_7":{"attribute_name":"論文抄録","attribute_value_mlt":[{"subitem_description":"ロスレス音声圧縮では，エントロピー符号化を適用するにあたり音声信号の残差をスパースにすることが重要である．残差の絶対値を最小化する適応アルゴリズムとして Sign Algorithm（SA）が知られているが，他のアルゴリズムと比べ収束性能が悪い．SA に自然勾配法を適用した Natural Gragient SA（NGSA）が提案され，人口データに対して収束性能の改善が示されたが，実応用研究はされていない．本研究では NGSA に基づく新しいロスレス音声コーデック ”NARU”（Natural-gradient AutoRegressive Unlossy Audio Compressor）を提案する．実装は C 言語でオープンソースである．NARU と既存のコーデックの圧縮率とデコード速度比較を行い，圧縮率において優れた性能を示し，デコード速度についても実用的であることを確かめた．","subitem_description_type":"Other"}]},"item_4_description_8":{"attribute_name":"論文抄録(英)","attribute_value_mlt":[{"subitem_description":"In lossless audio compression, it is essential for predictive residuals to remain sparse when applying entropy codings. The sign algorithm (SA) is a conventional method for minimizing the magnitude of residuals; however, it exhibits poor convergence performance compared with the other adaptive algorithms. Although the natural gradient sign algorithm (NGSA) exhibited better convergence performance than SA, its practical applications were not provided yet. This paper proposes a novel lossless audio codec based on the NGSA, called Natural-gradient AutoRegressive Unlossy Audio Compressor (NARU). Its implementation was written by C and open-source. We compared the NARU with existed well-known codecs and showed better compression performance.","subitem_description_type":"Other"}]},"item_4_biblio_info_10":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicPageEnd":"4","bibliographic_titles":[{"bibliographic_title":"研究報告数理モデル化と問題解決（MPS）"}],"bibliographicPageStart":"1","bibliographicIssueDates":{"bibliographicIssueDate":"2021-07-20","bibliographicIssueDateType":"Issued"},"bibliographicIssueNumber":"1","bibliographicVolumeNumber":"2021-MPS-134"}]},"relation_version_is_last":true,"weko_creator_id":"44499"},"created":"2025-01-19T01:13:10.537420+00:00","id":212160,"links":{}}