Input-Output HMM Applied to Automatic Arrangement for Guitars

• Item type: Journal(1)
• 公開日: 2013-04-15
• タイトル: Input-Output HMM Applied to Automatic Arrangement for Guitars
• タイトル / 言語: en
• タイトル: Input-Output HMM Applied to Automatic Arrangement for Guitars
• 言語: eng
• キーワード / 主題Scheme: Other
• キーワード / 主題: [特集：音楽情報処理の新展開（音楽情報科学研究会20周年記念特集）] guitar, fingering decision, arrangement, hidden Markov model, Viterbi algorithm
• 資源タイプ / 資源タイプ識別子: http://purl.org/coar/resource_type/c_6501
• 資源タイプ: journal article
• 著者所属: Faculty of Business Administration, Asia University
• 著者所属: Graduate School of Information Science and Technology, The University of Tokyo
• 著者所属: Graduate School of Information Science and Technology, The University of Tokyo
• 著者所属(英): en
• 著者所属(英): Faculty of Business Administration, Asia University
• 著者所属(英): en
• 著者所属(英): Graduate School of Information Science and Technology, The University of Tokyo
• 著者所属(英): en
• 著者所属(英): Graduate School of Information Science and Technology, The University of Tokyo
• 著者名: Gen, Hori; Hirokazu, Kameoka; Shigeki, Sagayama
• 著者名(英): Gen, Hori; Hirokazu, Kameoka; Shigeki, Sagayama
• 論文抄録 / 内容記述タイプ: Other
• 論文抄録 / 内容記述: Given a relatively small selection of guitar scores for a large population of guitarists, there should be a certain demand for systems that can automatically arrange an arbitrary score for guitars. Our aim in this paper is to formulate the “fingering decision” and “arrangement” in a unified framework that can be cast as a decoding problem of a hidden Markov model (HMM). The left hand forms on the fingerboard are considered as the hidden states and the note sequence of a given score as an observed sequence generated by the HMM. Finding the most likely sequence of the hidden states thus corresponds to performing fingering decision or arrangement. The manual setting of HMM parameters reflecting preference of beginner guitarists lets the framework generate natural fingerings and arrangements suitable for beginners. Some examples of fingering and arrangement produced by the proposed method are presented.; ------------------------------; This is a preprint of an article intended for publication Journal of; Information Processing(JIP). This preprint should not be cited. This; article should be cited as: Journal of Information Processing Vol.21(2013) No.2 (online); DOI http://dx.doi.org/10.2197/ipsjjip.21.264; ------------------------------
• 論文抄録(英) / 内容記述タイプ: Other
• 論文抄録(英) / 内容記述: Given a relatively small selection of guitar scores for a large population of guitarists, there should be a certain demand for systems that can automatically arrange an arbitrary score for guitars. Our aim in this paper is to formulate the “fingering decision” and “arrangement” in a unified framework that can be cast as a decoding problem of a hidden Markov model (HMM). The left hand forms on the fingerboard are considered as the hidden states and the note sequence of a given score as an observed sequence generated by the HMM. Finding the most likely sequence of the hidden states thus corresponds to performing fingering decision or arrangement. The manual setting of HMM parameters reflecting preference of beginner guitarists lets the framework generate natural fingerings and arrangements suitable for beginners. Some examples of fingering and arrangement produced by the proposed method are presented.; ------------------------------; This is a preprint of an article intended for publication Journal of; Information Processing(JIP). This preprint should not be cited. This; article should be cited as: Journal of Information Processing Vol.21(2013) No.2 (online); DOI http://dx.doi.org/10.2197/ipsjjip.21.264; ------------------------------
• 書誌レコードID / 収録物識別子タイプ: NCID
• 書誌レコードID / 収録物識別子: AN00116647
• 書誌情報: 情報処理学会論文誌; 巻 54, 号 4, 発行日 2013-04-15
• ISSN / 収録物識別子タイプ: ISSN
• ISSN / 収録物識別子: 1882-7764