Updated on 2025/06/30

Information

 

写真a

 
NAKAMURA EITA
 
Organization
Faculty of Information Science and Electrical Engineering Department of Informatics Associate Professor
Joint Graduate School of Mathematics for Innovation (Concurrent)
School of Engineering Department of Electrical Engineering and Computer Science(Concurrent)
Graduate School of Information Science and Electrical Engineering Department of Information Science and Technology(Concurrent)
Title
Associate Professor
Contact information
メールアドレス

Research Areas

  • Informatics / Intelligent informatics

  • Natural Science / Theoretical studies related to particle-, nuclear-, cosmic ray and astro-physics

Degree

  • Ph.D.

Research History

  • Kyushu University Graduate School of Information Science and Electrical Engineering Associate Professor 

    2024.4 - Present

  • Kyoto University The Hakubi Center for Advanced Research Specially Appointed Assistant Professor 

    2019.10 - 2024.3

  • Kyoto University Graduate School of Informatics Specially Appointed Assistant Professor 

    2019.4 - 2019.9

  • JSPS  Postdoctoral Research Fellow 

    2016.4 - 2019.3

  • Kyoto University  Academic Researcher 

    2015.8 - 2016.3

  • Meiji University Research and Intellectual Properties Academic Promotion Specialist 

    2014.11 - 2015.7

  • National Institute of Informatics  Specially Appointed Assistant Professor 

    2014.4 - 2014.10

  • National Institute of Informatics  Academic Researcher 

    2013.4 - 2014.3

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Education

  • The University of Tokyo   Graduate School of Information Science and Technology  

    2013.4 - 2014.3

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    Notes:Research Student

  • The University of Tokyo   Graduate School of Science   Department of Physics

    - 2012.3

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    Notes:Ph.D in physics

  • The University of Tokyo   Graduate School of Science   Department of Physics

    - 2009.3

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    Notes:Master's degree

  • The University of Tokyo   School of Science   Department of Physics

    - 2007.3

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    Notes:Bachelor's degree

Research Interests・Research Keywords

  • Research theme: Cultural Evolution Science

    Keyword: Evolutionary dynamics, stochastic model of cultural evolution, evolutionary analysis of creative styles, evolutionary prediction, reference network analysis

    Research period: 2015 - Present

  • Research theme: Music Informatics

    Keyword: Music transcription, music alignment, automatic composition, automatic music arrangement, automatic accompaniment, piano fingering estimation

    Research period: 2012 - Present

  • Research theme: Elementary particle theory

    Keyword: Supersymmetric standard model

    Research period: 2007 - 2012

Awards

  • 学生奨励賞

    2025.3   情報処理学会   作曲スタイル認識を導入したRNNトランスデューサに基づく歌声MIDI採譜

    杉本悠, 中村栄太

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    Award type:Award from Japanese society, conference, symposium, etc. 

  • 学生奨励賞

    2025.3   情報処理学会   ArtEvoViewer : 画家個人間の影響関係を可視化するシステム

    小田稜子, 中村栄太, 伊藤貴之

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    Award type:Award from Japanese society, conference, symposium, etc. 

  • 学生奨励賞

    2025.3   情報処理学会   歌詞の条件付きメロディ生成モデルに基づく歌唱曲の評価手法

    西村草介, 中村栄太

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    Award type:Award from Japanese society, conference, symposium, etc. 

  • Best Paper Award

    2023.11   15th International Symposium on Computer Music Multidisciplinary Research (CMMR)  

  • Best Presentation Award

    2021.9   IPSJ Special Interest Group on Music and Computer (SIGMUS)  

  • Best Presentation Award

    2018.8   IPSJ Special Interest Group on Music and Computer (SIGMUS)  

  • Yamashita Memorial Award

    2015   Information Processing Society of Japan  

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Papers

  • On the importance of time and pitch relativity for transformer-based symbolic music generation Reviewed

    Tatsuro Inaba, Kazuyoshi Yoshii, Eita Nakamura

    Proc. 16th Asia Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA ASC)   2024.12   ISSN:2309-9402 ISBN:979-8-3503-6734-8

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    Authorship:Last author   Language:English   Publishing type:Research paper (international conference proceedings)   Publisher:Apsipa ASC 2024 Asia Pacific Signal and Information Processing Association Annual Summit and Conference 2024  

    This paper describes experimental investigation of music representations to draw the full potential of the Transformer with the self-attention mechanism for symbolic music generation. To use sequence-to-sequence model like the Transformer originally proposed for natural language processing, one typically serializes a musical score into a sequence of event- or note-based tokens without concern for the impact on the quality of generated music. The semantic invariance of music with respect to the time and pitch shifts is attributed to the positional relativity of musical notes over the time-pitch plane in which beats and pitch classes are repeated at intervals of bars and octaves, respectively. We here hypothesize that the capability of the self-attention mechanism to learn the musically meaningful rhythm, melody, and harmony is limited because the relativity and cyclicity of time and pitch information are not explicitly represented in the token sequence. To solve this problem, we propose a cyclicity-aware relative time and pitch encoding unique to music for the attention mechanism. Comprehensive evaluation using the POP909 dataset demonstrated that the proposed Transformer works better with event- or note-based score tokenization.

    DOI: 10.1109/APSIPAASC63619.2025.10849230

    Web of Science

    Scopus

  • Modeling the evolution of harmony in popular music from different cultural contexts Reviewed International coauthorship

    Fabian C. Moss, Eita Nakamura

    Proc. 5th Conference on Computational Humanities Research (CHR)   137 - 152   2024.12

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    Authorship:Last author   Language:English   Publishing type:Research paper (international conference proceedings)   Publisher:Ceur Workshop Proceedings  

    Popular music often features a high amount of stable harmonic patterns, which facilitates the establishment of stylistic idioms and recognizability, and the changing frequencies of such patterns are closely linked to style and genre: new patterns arise while others die out. Here, we employ a content-based transmission model from cultural evolution research and compare three 20th-century popular music genres from different geographical and cultural contexts. Prior work on the evolution of harmony often only considers a small vocabulary of chords with a binary distance metric (same or different). Here, we introduce music-theoretically sensible notions of harmonic distance between chords, that allows us to arrive at more fine-grained results regarding relative influences of different kinds of harmonic relations on diachronic changes. Inferring the substitution probabilities for different chord classes, our results indicate an increasing usage of chord categories, whereas chord extensions remain relatively stable. Our study provides a principled methodology for cross-cultural research on the evolution of harmony.

    Scopus

  • Cluster and separate: a GNN approach to voice and staff prediction for score engraving Reviewed International coauthorship

    Francesco Foscarin, Emmanouil Karystinaios, Eita Nakamura, Gerhard Widmer

    Proc. 25th International Society for Music Information Retrieval Conference (ISMIR)   503 - 510   2024.11

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    Language:English   Publishing type:Research paper (international conference proceedings)  

  • End-to-end singing transcription based on CTC and HSMM decoding with a refined score representation Invited Reviewed

    Tengyu Deng, Eita Nakamura, Ryo Nishikimi, Kazuyoshi Yoshii

    APSIPA Transactions on Signal and Information Processing   13 ( 5(e404) )   1 - 16   2024.5   ISSN:2048-7703

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    Language:English   Publishing type:Research paper (scientific journal)   Publisher:Apsipa Transactions on Signal and Information Processing  

    This paper describes an end-to-end automatic singing transcription (AST) method that translates a music audio signal containing a vocal part into a symbolic musical score of sung notes. A common approach to sequence-to-sequence learning for this problem is to use the connectionist temporal classification (CTC), where a target score is represented as a sequence of notes with discrete pitches and note values. However, if the note value of some note is incorrectly estimated, the score times of the following notes are estimated incorrectly and the metrical structure of the estimated score collapses. To solve this problem, we propose a refined score representation using metrical positions of note onsets. To decode a musical score from the output of a deep neural network (DNN), we use a hidden semi-Markov model (HSMM) that incorporates prior knowledge about musical scores and temporal fluctuation in human performance. We show that the proposed method achieves the state-of-the-art performance and confirm the efficacy of the refined score representation and the decoding method.

    DOI: 10.1561/116.20240016

    Web of Science

    Scopus

  • Estimation of creator influences based on cultural evolution models of color styles in painting arts Reviewed

    Eita Nakamura, Yasuyuki Saito

    The Journal of the Institute of Image Electronics Engineers of Japan   53 ( 1 )   19 - 27   2024.2

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    Authorship:Lead author, Corresponding author   Language:Japanese   Publishing type:Research paper (scientific journal)  

  • Computational analysis of selection and mutation probabilities in the evolution of chord progressions Reviewed

    Eita Nakamura

    Proc. 16th International Symposium on Computer Music Multidisciplinary Research (CMMR)   462 - 473   2023.11

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    Authorship:Lead author, Corresponding author   Language:English   Publishing type:Research paper (international conference proceedings)  

  • Audio-to-score singing transcription based on joint estimation of pitches, onsets, and metrical positions with tatum-level CTC loss Reviewed

    Tengyu Deng, Eita Nakamura, Kazuyoshi Yoshii

    Proc. 15th Asia Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA)   570 - 577   2023.11

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    Language:English   Publishing type:Research paper (international conference proceedings)  

  • Evolutionary analysis and cultural transmission models of color style distributions in painting arts Reviewed

    Eita Nakamura, Yasuyuki Saito

    Proc. 15th Asia Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA)   493 - 500   2023.11

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    Authorship:Lead author, Corresponding author   Language:English   Publishing type:Research paper (international conference proceedings)  

  • CTC2: End-to-end drum transcription based on connectionist temporal classification with constant tempo constraint, Reviewed

    Daichi Kamakura, Eita Nakamura, Kazuyoshi Yoshii,

    Proc. 15th Asia Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA)   152 - 158   2023.11

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    Language:English   Publishing type:Research paper (international conference proceedings)  

  • Joint drum transcription and metrical analysis based on periodicity-aware multi-task learning Reviewed

    Daichi Kamakura, Takehisa Ooyama, Eita Nakamura, Kazuyoshi Yoshii

    Proc. 15th Asia Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA)   145 - 151   2023.11

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    Language:English   Publishing type:Research paper (international conference proceedings)  

  • Automatic orchestration of piano scores for wind bands with user-specified instrumentation Reviewed

    Takuto Nabeoka, Eita Nakamura, Kazuyoshi Yoshii

    Proc. 16th International Symposium on Computer Music Multidisciplinary Research (CMMR)   387 - 394   2023.11

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    Authorship:Corresponding author   Language:English   Publishing type:Research paper (international conference proceedings)  

  • Historical changes of modes and their substructure modeled as pitch distributions in plainchant from the 1100s to the 1500s Reviewed International coauthorship

    Eita Nakamura, Tim Eipert, Fabian C. Moss

    Proc. 16th International Symposium on Computer Music Multidisciplinary Research (CMMR)   450 - 461   2023.11

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    Authorship:Lead author   Language:English   Publishing type:Research paper (international conference proceedings)  

  • Mutual generation in neuronal activity across the brain via deep neural approach, and its network interpretation Reviewed

    Ryota Nakajima, Arata Shirakami, Hayato Tsumura, Kouki Matsuda, Eita Nakamura, Masanori Shimono

    Communications Biology   6 ( 1105 )   1 - 14   2023.10

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    Language:English   Publishing type:Research paper (scientific journal)  

    DOI: 10.1038/s42003-023-05453-2

  • Computational analysis of audio recordings of piano performance for automatic evaluation Reviewed

    Norihiro Kato, Eita Nakamura, Kyoko Mine, Orie Doeda, Masanao Yamada

    Proc. 18th European Conference on Technology Enhanced Learning (ECTEL)   586 - 592   2023.9

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    Language:English   Publishing type:Research paper (international conference proceedings)  

  • Experimental evolution of music styles using automatic composition models Reviewed

    Eita Nakamura, Hitomi Kaneko, Takayuki Itoh, Kunihiko Kaneko

    Proc. 2023 Conference on Artificial Life (ALIFE)   660 - 662   2023.7

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    Authorship:Lead author, Corresponding author   Language:English   Publishing type:Research paper (international conference proceedings)  

  • Neural band-to-piano score arrangement with stepless difficulty control Reviewed

    Moyu Terao, Eita Nakamura, Kazuyoshi Yoshii

    Proc. 48th IEEE International Conference on Acoustics, Speech, and Signal Processing Conference (ICASSP)   ( 1415 )   1 - 5   2023.6

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    Language:English   Publishing type:Research paper (international conference proceedings)  

  • Automatic orchestration of piano scores for wind bands with user-specified instrumentation Reviewed

    中村 栄太

    16th International Symposium on Computer Music Multidisciplinary Research (CMMR)   0   387 - 394   2023

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  • Historical changes of modes and their substructure modeled as pitch distributions in plainchant from the 1100s to the 1500s Reviewed International coauthorship

    中村 栄太

    16th International Symposium on Computer Music Multidisciplinary Research (CMMR)   0   450 - 461   2023

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  • Experimental evolution of music styles using automatic composition models Reviewed

    中村 栄太, 伊藤 貴之

    2023 Conference on Artificial Life (ALIFE)   0   660 - 662   2023

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  • Computational analysis of selection and mutation probabilities in the evolution of chord progressions Reviewed

    中村 栄太

    16th International Symposium on Computer Music Multidisciplinary Research (CMMR)   0   462 - 473   2023

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  • End-to-end lyrics transcription informed by pitch and onset estimation, Reviewed

    Tengyu Deng, Eita Nakamura, Kazuyoshi Yoshii

    Proc. 23rd International Society for Music Information Retrieval Conference (ISMIR)   633 - 639   2022.12

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    Language:English   Publishing type:Research paper (international conference proceedings)  

  • Tracking the evolution of a band's performances over decades Reviewed International coauthorship

    Florian Thalmann, Eita Nakamura, Kazuyoshi Yoshii

    Proc. 23rd International Society for Music Information Retrieval Conference (ISMIR)   850 - 857   2022.12

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    Language:English   Publishing type:Research paper (international conference proceedings)  

  • Automatic piano fingering from partially annotated scores using autoregressive neural networks Reviewed International coauthorship

    Pedro Ramoneda, Dasaem Jeong, Eita Nakamura, Xavier Serra, Marius Miron

    Proc. 30th ACM International Conference on Multimedia (ACMMM)   6502 - 6510   2022.10

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    Language:English   Publishing type:Research paper (international conference proceedings)  

  • Dynamic cluster structure and predictive modelling of music creation style distributions Reviewed

    Rajsuryan Singh, Eita Nakamura

    Royal Society Open Science   9 ( 220516 )   1 - 18   2022

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    Authorship:Last author, Corresponding author   Language:English   Publishing type:Research paper (scientific journal)  

    DOI: 10.1098/rsos.220516

  • Joint Estimation of Note Values and Voices for Audio-to-Score Piano Transcription Reviewed

    Yuki Hiramatsu, Eita Nakamura, Kazuyoshi Yoshii

    Proc. 22nd International Society for Music Information Retrieval Conference (ISMIR)   278 - 284   2021.11

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    Language:English   Publishing type:Research paper (international conference proceedings)  

  • Eita Nakamura Reviewed

    Conjugate Distribution Laws in Cultural Evolution via Statistical Learning

    Physical Review E   104 ( 034309 )   1 - 13   2021.9

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    Authorship:Lead author, Corresponding author   Language:English   Publishing type:Research paper (scientific journal)  

    DOI: 10.1103/PhysRevE.104.034309

  • Statistical Correction of Transcribed Melody Notes Based on Probabilistic Integration of a Music Language Model and a Transcription Error Model Reviewed

    Yuki Hiramatsu, Go Shibata, Ryo Nishikimi, Eita Nakamura, Kazuyoshi Yoshii

    Proc. 46th IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)   256 - 260   2021.6

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    Language:English   Publishing type:Research paper (international conference proceedings)  

  • Eita Nakamura, Kazuyoshi Yoshii Reviewed

    Music Transcription Based on Bayesian Piece-Specific Score Models Capturing Repetitions

    Information Sciences   572   482 - 500   2021.5

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    Authorship:Lead author, Corresponding author   Language:English   Publishing type:Research paper (scientific journal)  

    DOI: 10.1016/j.ins.2021.04.100

  • Audio-to-Score Singing Transcription Based on a CRNN-HSMM Hybrid Model Reviewed

    Ryo Nishikimi, Eita Nakamura, Masataka Goto, Kazuyoshi Yoshii

    APSIPA Transactions on Signal and Information Processing   10 ( e7 )   1 - 13   2021.4

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    Language:English   Publishing type:Research paper (scientific journal)  

    DOI: 10.1017/ATSIP.2021.4

  • Non-Local Musical Statistics as Guides for Audio-to-Score Piano Transcription Reviewed

    Kentaro Shibata, Eita Nakamura, Kazuyoshi Yoshii

    Information Sciences   566   262 - 280   2021.3

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    Authorship:Corresponding author   Language:English   Publishing type:Research paper (scientific journal)  

    DOI: 10.1016/j.ins.2021.03.014

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Presentations

  • ピアノ演奏MIDIデータに基づいたフレーズ・アーチングの分析

    高橋舞, 小林未知数, 大向一輝, 中村栄太

    第142回情報処理学会音楽情報科学研究会  2025.3 

  • ArtEvoViewer : 画家個人間の影響関係を可視化するシステム

    小田稜子, 中村栄太, 伊藤貴之

    第87回情報処理学会全国大会  2025.3 

  • 歌詞の条件付きメロディ生成モデルに基づく歌唱曲の評価手法

    西村草介, 中村栄太

    第87回情報処理学会全国大会  2025.3 

  • 作曲スタイル認識を導入したRNNトランスデューサに基づく歌声MIDI採譜

    杉本悠, 中村栄太

    第87回情報処理学会全国大会  2025.3 

  • 統計モデリングと機械学習に基づく音楽進化解析 Invited

    中村栄太

    日本音響学会第152回研究発表会  2024.9 

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    Language:Japanese   Presentation type:Oral presentation (invited, special)  

  • Recent developments and open problems in audio-to-score music transcription Invited International conference

    Eita Nakamura

    Eighth International Workshop on Symbolic-Neural Learning (SNL2024)  2024.6 

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    Language:English   Presentation type:Oral presentation (invited, special)  

  • AIは音楽文化をどう変えるか? Invited

    中村栄太

    日本ポピュラー音楽学会  2024.12 

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    Language:Japanese   Presentation type:Oral presentation (invited, special)  

  • Automatic transcription and alignment for analyzing piano performance Invited International conference

    Eita Nakamura

    Symposium on Analysing Interpretations  2024.12 

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    Language:English   Presentation type:Oral presentation (invited, special)  

  • 創作知識の進化モデルに基づく音楽スタイルの進化解析 Invited

    中村栄太

    経済・社会の分野横断的研究会  2024.12 

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    Language:Japanese   Presentation type:Oral presentation (invited, special)  

  • 記号音楽生成における時間と音高相対性の重要性

    稲葉達郎, 吉井和佳, 中村栄太

    第141回情報処理学会音楽情報科学研究会  2024.8 

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    Language:Japanese   Presentation type:Oral presentation (general)  

  • Bayesian model of multiparental cultural transmission for reference network estimation International conference

    Eita Nakamura

    Cultural Evolution Society Conference (CES)  2024.9 

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    Language:English   Presentation type:Oral presentation (general)  

  • Analysis of Performance Style by MIDI Piano Recordings International conference

    Mai Takahashi, Michikazu Kobayashi, Eita Nakamura, Ikki Ohmukai

    13th Annual Conference of the Japanese Association for Digital Humanities (JADH)  2024.9 

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    Language:English   Presentation type:Oral presentation (general)  

  • 西洋絵画における作者の影響関係を可視化するユーザインタフェース

    小田稜子, 中村栄太, 伊藤貴之

    第32回インタラクティブシステムとソフトウェアに関するワークショップ (WISS 2024)  2024.12 

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    Language:Japanese   Presentation type:Poster presentation  

  • 歌詞の音韻特徴量に対する適合度を考慮した歌唱曲の生成と自動評価

    西村草介, 中村栄太

    第142回情報処理学会音楽情報科学研究会  2025.3 

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    Language:Japanese   Presentation type:Poster presentation  

  • 歌声MIDI採譜における作曲スタイルを導入した言語モデルの効果の検証

    杉本悠, 中村栄太

    第142回情報処理学会音楽情報科学研究会  2025.3 

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    Language:Japanese   Presentation type:Poster presentation  

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MISC

  • 音楽生成研究の動向と展望 Invited Reviewed

    中村栄太

    映像情報メディア学会誌   78 ( 4 )   2024.7

  • 創作文化の進化科学 Invited Reviewed

    中村栄太

    数理科学2024年4月号   2024.4

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    Language:Japanese  

Industrial property rights

Patent   Number of applications: 2   Number of registrations: 2
Utility model   Number of applications: 0   Number of registrations: 0
Design   Number of applications: 0   Number of registrations: 0
Trademark   Number of applications: 0   Number of registrations: 0

Professional Memberships

  • The Japanese Society for Artificial Intelligence

  • Information Processing Society of Japan

  • The Physical Society of Japan

Committee Memberships

  • 情報処理学会   論文誌編集委員  

    2025.6 - Present   

  • 情報処理学会音楽情報科学研究会   幹事  

    2025.4 - 2027.3   

  • 情報処理学会音楽情報科学研究会   運営委員  

    2022.4 - 2025.3   

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    Committee type:Academic society

  • 情報処理学会音楽情報科学研究会   運営委員  

    2015.4 - 2016.3   

Academic Activities

  • 音学シンポジウム実行副委員長

    Role(s): Planning, management, etc.

    2025.6

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    Type:Academic society, research group, etc. 

  • International Society for Music Information Retrieval Conference 2025 Meta Reviewer International contribution

    Role(s): Peer review

    2025

  • APSIPA ASC 2025 Meta Reviewer International contribution

    Role(s): Peer review

    2025

  • 電気情報通信学会論文誌査読

    Role(s): Peer review

    2024.7

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    Type:Peer review 

    Number of peer-reviewed articles in Japanese journals:1

  • 音学シンポジウム実行副委員長

    Role(s): Planning, management, etc.

    情報処理学会  2024.6

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    Type:Competition, symposium, etc. 

    Number of participants:312

  • Neuroscience Reviewer International contribution

    Role(s): Peer review

    2024

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    Type:Peer review 

    Number of peer-reviewed articles in foreign language journals:1

  • Journal of Neuroscience Methods Reviewer International contribution

    Role(s): Peer review

    2024

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    Type:Peer review 

    Number of peer-reviewed articles in foreign language journals:1

  • Eurasip Journal Reviewer International contribution

    Role(s): Peer review

    2024

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    Type:Peer review 

    Number of peer-reviewed articles in foreign language journals:1

  • Physica A Reviewer International contribution

    Role(s): Peer review

    2024

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    Type:Peer review 

    Number of peer-reviewed articles in foreign language journals:1

  • ICASSP 2025 Reivewer International contribution

    Role(s): Peer review

    2024

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    Type:Peer review 

    Proceedings of International Conference Number of peer-reviewed papers:4

  • 音学シンポジウム実行副委員長

    Role(s): Planning, management, etc.

    2023.6

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    Type:Academic society, research group, etc. 

  • 音学シンポジウム実行副委員長

    Role(s): Planning, management, etc.

    2022.6

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    Type:Academic society, research group, etc. 

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Other

  • Music Information Processing Research on Piano Performance Instruction and Practice Support

    2024.12 - 2026.3

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    Research at PTNA Research Institute of Music

Research Projects

  • 構成論的アプローチによる進化音楽学の構築

    Grant number:25H01169  2025.4 - 2030.3

    Grants-in-Aid for Scientific Research  Grant-in-Aid for Scientific Research (A)

    東条 敏, 北原 鉄朗, 中村 栄太, 上原 由衣, 秦野 亮, 澤田 隼, 堀 玄, 大村 英史

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    Authorship:Coinvestigator(s)  Grant type:Scientific research funding

    進化言語学における構成論的アプローチとは,進化と創発の過程を形式化・モデル化し計算機シミュレーションで実証する方法論である.本研究ではこれを音楽に応用し,音楽の進化,すなわち楽曲の通時的変化の過程が計算機の中で模倣できるかどうかを検証する.本研究では特に人口動力学や世代交代モデルを用い,さまざまなタイムスケールで音楽の進化シミュレーションを行い,進化言語学の方法論が楽曲についても有用であることを示す.

  • Study on Automatic Music Transcription Based on the Hierarchical Integration of Theoretical Models of Music Production Process and Deep Learning

    Grant number:25H01148  2025.4 - 2029.3

    Grants-in-Aid for Scientific Research  Grant-in-Aid for Scientific Research (A)

    中村 栄太, 金子 仁美, 中島 悠太, 伊藤 貴之, 中鹿 亘

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    Authorship:Principal investigator  Grant type:Scientific research funding

    音楽情報処理の基盤技術である自動採譜(音響データから演奏・楽譜情報を認識する技術)の実用化を実現すべく、多種多様な音楽データに対する深層学習手法の汎用性を向上させる体系的方法を研究する。当該分野の根本的課題である、大規模データに依存する研究方法の限界を突破するため、本研究では音楽の多様性を音楽制作過程のレイヤ(楽譜・演奏・音響)に分けて整理し、各レイヤで定式化する理論モデルを深層学習の制約化・転移学習・データ拡張などに統合利用する方法を調べる。

    CiNii Research

  • 理論と社会的実験で築く知能と文化の進化動力学 International coauthorship

    Grant number:JPMJPR226X  2023.4 - 2026.3

    JST  創発的研究支援事業 

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    Authorship:Principal investigator  Grant type:Contract research

  • 深層・統計学習と非平衡系物理の理論に基づく文化と知能の進化モデルの研究 International coauthorship

    Grant number:23K24917  2022.4 - 2025.3

    Grants-in-Aid for Scientific Research  Grant-in-Aid for Scientific Research (B)

    中村 栄太, 金子 仁美, 齋藤 康之, 伊藤 貴之, 持橋 大地

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    Authorship:Principal investigator  Grant type:Scientific research funding

    高度な知能を要する文化の発展の原理を理解するとともに、スタイルが時間変化する創作物データの情報処理と予測を可能にするため、深層・統計モデルと進化理論を統合した「文化と知能の進化モデル」を研究する。本研究では、このモデルの構築と解析のための理論手法と機械学習手法を研究して、(A) 多分野で活用できる文化進化の解析手法の構築、(B) 音楽・言語・絵画データの正確なトレンド予測、(C) 芸術史における変革期の定量的な要因分析、(D) 作曲・演奏スタイルの時代変化に対応できる音楽情報処理技術の開発を行う。

    CiNii Research

Educational Activities

  • Teaching in the Department of Information Science and Technology, Graduate School of Information Science and Electrical Engineering, and in the Department of Electrical Engineering and Computer Science, School of Engineering.

Class subject

  • 【通年】情報理工学講究

    2025.4 - 2026.3  

  • 【通年】情報理工学研究Ⅰ

    2025.4 - 2026.3   Full year

  • 【通年】情報理工学演習

    2025.4 - 2026.3  

  • 基礎PBLⅢ

    2025.4 - 2025.9   First semester

  • 電気情報工学セミナーA

    2024.10 - 2025.3   Second semester

  • 国際科学特論II

    2024.10 - 2025.3   Second semester

  • 【通年】情報理工学講究

    2024.4 - 2025.3   Full year

  • 【通年】情報理工学演習

    2024.4 - 2025.3   Full year

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FD Participation

  • 2025.6   Role:Participation   Title:【シス情FD】学際情報学特別部門の紹介

    Organizer:[Undergraduate school/graduate school/graduate faculty]

  • 2025.2   Role:Participation   Title:【シス情FD】プレアドミッション・サポートデスク(PSD)による留学生のための出願前支援 〜導入のメリット〜

    Organizer:[Undergraduate school/graduate school/graduate faculty]

  • 2025.1   Role:Participation   Title:【シス情FD】日本学術振興会の人材育成事業と男女共同参画推進に関するご紹介 ― 特別研究員制度、日本学術振興会賞ほか ―

    Organizer:[Undergraduate school/graduate school/graduate faculty]

  • 2024.9   Role:Participation   Title:九州大学公開全学FD(未来人材育成機構) 「共創学部—その新しい取り組みと展望」

    Organizer:University-wide

  • 2024.5   Role:Participation   Title:【シス情FD】科研費の最近の動向について

    Organizer:[Undergraduate school/graduate school/graduate faculty]

  • 2024.4   Role:Participation   Title:令和6年度 第1回全学FD(新任教員の研修)

    Organizer:University-wide

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Teaching Student Awards

  • 学生奨励賞

    Year and month of award:2025.3

    Classification of award-winning students:Undergraduate student   Name of award-winning student:杉本悠

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    情報処理学会全国大会

  • 学生奨励賞

    Year and month of award:2025.3

    Classification of award-winning students:Undergraduate student   Name of award-winning student:西村草介

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    情報処理学会全国大会

Outline of Social Contribution and International Cooperation activities

  • Joint research with institutions such as the University of Linz, Academia Sinica (Taiwan), the University of Würzburg, and the Korea Advanced Institute of Science and Technology (KAIST).

Media Coverage

  • 生成AIに楽譜をつくらせる挑戦 最初は「出番ゼロ」になる楽器も… Newspaper, magazine

    朝日新聞デジタル  2023.8

  • ピアノ演奏、AIが採譜 京大チーム、他の楽器にも対応へ Newspaper, magazine

    日本経済新聞  2021.7

Travel Abroad

  • 2016.11 - 2017.10

    Staying countory name 1:United Kingdom   Staying institution name 1:Queen Mary University of London