著書
- [PDF] [GTTM] [deep GTTM] Masatoshi Hamanaka, Keiji Hirata, Satoshi Tojo: “deepGTTM-III: Multi-task Learning with Grouping and Metrical Structures”, Lecture Notes in Computer Science (LNCS), Vol.11265, pp.238-251, Springer, 2018.
- [PDF] [GTTM] [deep GTTM] Masatoshi Hamanaka, Keiji Hirata, Satoshi Tojo: “deepGTTM-I&II: Local Boundary and Metrical Structure Analyzer based on Deep Learning Technique”, Lecture Notes in Computer Science (LNCS), Vol.10525, pp.3-21, Springer, 2017.
国際会議論文
- [LINK] [GTTM] [deepGTTM] Masatoshi Hamanaka, Keiji Hirata and Satoshi Tojo: “Time-span Tree Leveled by Duration of Time-span”, the 15th International Symposium on Computer Music Multidisciplinary Research (CMMR2021), pp.155-164, November 2021.
- [PDF] [GTTM] [deep GTTM] Masatoshi Hamanaka, Keiji Hirata, Satoshi Tojo: “deepGTTM-III: Simultaneous Learning of Grouping and Metrical Structures”, the 13th International Symposium on Computer Music Multidisciplinary Research (CMMR2017), pp.161-172, September 2017.
- [PDF] [exGTTM] Masatoshi Hamanaka, Keiji Hirata, Satoshi Tojo: “Polyphonic Music Analysis Database Based on GTTM”, the 2nd Conference on Computer Simulation of Musical Creativity (CSMC2017), 8 pages, September 2017.
- [PDF] [GTTM] [deep GTTM] Masatoshi Hamanaka, Keiji Hirata, Satoshi Tojo: “deepGTTM-II: Automatic Generation of Metrical Structure based on Deep Learning Technique”, the 13th Sound and Music Conference (SMC2016), pp.221-249, 2016.
- [PDF] [GTTM] [deep GTTM] Masatoshi Hamanaka, Keiji Hirata, Satoshi Tojo: “deepGTTM-I&II: Local Boundary and Metrical Structure Analyzer based on Deep Learning Technique”, 13th International Symposium on Computer Music Multidisciplinary Research (CMMR2016), pp.3-21, July 2016.
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[PDF] [GTTM] [deep GTTM] Masatoshi Hamanaka, Keiji Hirata, Satoshi Tojo: “deepGTTM-I: Local Boundaries Analyzer based on Deep Learning Technique”, 13th International Symposium on Computer Music Multidisciplinary Research (CMMR2016), pp.8-20, July 2016.
国内会議論文
- [PDF(AIgakkai)] [GTTM] [deep GTTM] 中村栄太, 浜中雅俊, 平田圭二, 吉井和佳: “GTTMに基づくメロディ音符列の確率的木構造モデル”, JSAI2016 人工知能学会全国大会第30回, 3G4-OS-15b-4, June 2016.
- [PDF] [GTTM] [deep GTTM] 浜中雅俊: “deepGTTM-:ディープラーニングに基づく局所的グルーピング境界分析器”, JSAI2016 人工知能学会全国大会第30回, 3G4-OS-15b-3, June 2016.
- [LINK] [GTTM] [deep GTTM] 浜中雅俊, 平田圭二, 東条敏: “deepGTTM-II: ディープラーニングに基づく拍節構造分析器”, 情報処理学会 音楽情報科学研究会研究報告 2016-MUS-112, Vol.2016, No.5, pp. 1-8, March 2016.