{"updated":"2025-01-19T10:24:41.609541+00:00","links":{},"created":"2025-01-19T01:33:28.706097+00:00","metadata":{"_oai":{"id":"oai:ipsj.ixsq.nii.ac.jp:00232547","sets":["1164:5159:11541:11549"]},"path":["11549"],"owner":"44499","recid":"232547","title":["ピアノ音に対する音階と残響のモーフィング"],"pubdate":{"attribute_name":"公開日","attribute_value":"2024-02-22"},"_buckets":{"deposit":"b0169334-7bc1-4ad1-b08e-3460f703e224"},"_deposit":{"id":"232547","pid":{"type":"depid","value":"232547","revision_id":0},"owners":[44499],"status":"published","created_by":44499},"item_title":"ピアノ音に対する音階と残響のモーフィング","author_link":["629689","629692","629690","629691"],"item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"ピアノ音に対する音階と残響のモーフィング"},{"subitem_title":"Acoustic morphing based on autoencoder for piano scale and reverberation","subitem_title_language":"en"}]},"item_keyword":{"attribute_name":"キーワード","attribute_value_mlt":[{"subitem_subject":"ポスターセッション3 EA/SIP","subitem_subject_scheme":"Other"}]},"item_type_id":"4","publish_date":"2024-02-22","item_4_text_3":{"attribute_name":"著者所属","attribute_value_mlt":[{"subitem_text_value":"同志社大学理工学部"},{"subitem_text_value":"同志社大学理工学部"}]},"item_4_text_4":{"attribute_name":"著者所属(英)","attribute_value_mlt":[{"subitem_text_value":"Faculty of Science and Engineering, Doshisha University","subitem_text_language":"en"},{"subitem_text_value":"Faculty of Science and Engineering, Doshisha University","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/232547/files/IPSJ-SLP24151077.pdf","label":"IPSJ-SLP24151077.pdf"},"format":"application/pdf","billing":["billing_file"],"filename":"IPSJ-SLP24151077.pdf","filesize":[{"value":"3.3 MB"}],"mimetype":"application/pdf","priceinfo":[{"tax":["include_tax"],"price":"0","billingrole":"22"},{"tax":["include_tax"],"price":"0","billingrole":"44"}],"accessrole":"open_login","version_id":"35a1eb5c-674c-4469-a4d8-e9d1d99aa628","displaytype":"detail","licensetype":"license_note","license_note":"Copyright (c) 2024 by the Institute of Electronics, Information and Communication Engineers This SIG report is only available to those in membership of the SIG."}]},"item_4_creator_5":{"attribute_name":"著者名","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"箱田, 由馬"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"土屋, 隆生"}],"nameIdentifiers":[{}]}]},"item_4_creator_6":{"attribute_name":"著者名(英)","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"Yuma, Hakoda","creatorNameLang":"en"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"Takao, Tsuchiya","creatorNameLang":"en"}],"nameIdentifiers":[{}]}]},"item_4_source_id_9":{"attribute_name":"書誌レコードID","attribute_value_mlt":[{"subitem_source_identifier":"AN10442647","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":"2188-8663","subitem_source_identifier_type":"ISSN"}]},"item_4_description_7":{"attribute_name":"論文抄録","attribute_value_mlt":[{"subitem_description":"ゲーム音響では，動的に変化するシーン内の音響をサウンドデザイナーが手動で操作している場合が多く，その自動化が望まれている．本研究では，その第一歩として機械学習を用いた音声データの生成について検討する．学習対象は，簡易的に生成が可能なピアノ音とする．学習データとなる音階ごとのピアノ音を短時間フーリエ変換した後，音圧の実部と虚部を同時に実数型オートエンコーダにより学習させた．損失関数としていくつかの誤差関数を用いて，ピアノ音を学習・生成させた結果，生成音の音質や音階の分類精度が変化することが示された．また，学習されたモデルを用いて，音階や残響を徐々に変化させる音響モーフィングを試みた結果，本手法では学習データに近いピアノ音は生成できたが，中間音については良好な結果が得られなかった．","subitem_description_type":"Other"}]},"item_4_description_8":{"attribute_name":"論文抄録(英)","attribute_value_mlt":[{"subitem_description":"In game audio, it is common for sound designers to manually express game sounds that change dynamic in game scenes. They desire automatic sound generation. Therefore, in this study, we focus on sound generation using machine learning. Initially, we use piano sounds that can be generated simply as input. After performing short-time Fourier transform on piano sounds, the real and imaginary parts of the sound pressure were simultaneously trained using autoencoder. Results comparing various machine learning methods for sound generation revealed differences in the quality of generated sounds and the classification accuracy for different musical scale. Further- more, researching on how sounds gradually change for piano scale and reverberation using this method indicated the difficulty of generating sounds except the training data.","subitem_description_type":"Other"}]},"item_4_biblio_info_10":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicPageEnd":"6","bibliographic_titles":[{"bibliographic_title":"研究報告音声言語情報処理（SLP）"}],"bibliographicPageStart":"1","bibliographicIssueDates":{"bibliographicIssueDate":"2024-02-22","bibliographicIssueDateType":"Issued"},"bibliographicIssueNumber":"77","bibliographicVolumeNumber":"2024-SLP-151"}]},"relation_version_is_last":true,"weko_creator_id":"44499"},"id":232547}