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Merged-Output Hmm For Piano Fingering Of Both Hands

Eita Nakamura, Nobutaka Ono, Shigeki Sagayama
2014 Zenodo  
First we reviewed a piano fingering model for one hand based on HMM, and then constructed a model for both hands based on merged-output HMM.  ...  The basic idea is to construct a model for both hands by starting with two parallel HMMs, called part HMMs, each of which corresponds to the HMM for fingering of each hand, and then merging the outputs  ... 
doi:10.5281/zenodo.1415151 fatcat:aoskygj52nhcxi2qfq43sqxm54

Statistical Learning and Estimation of Piano Fingering [article]

Eita Nakamura, Yasuyuki Saito, Kazuyoshi Yoshii
2020 arXiv   pre-print
Automatic estimation of piano fingering is important for understanding the computational process of music performance and applicable to performance assistance and education systems.  ...  interdependence of the two hands.  ...  Acknowledgment We thank Shigeki Sagayama and Kenji Watanabe for useful discussions, Shinichi Furuya and others for helping us collect fingering data, Dorien Herremans for providing the source code for  ... 
arXiv:1904.10237v2 fatcat:xs6g6qyzlfdcbmj3rtgfmfygg4

Statistical Piano Reduction Controlling Performance Difficulty [article]

Eita Nakamura, Kazuyoshi Yoshii
2018 arXiv   pre-print
dependence of pitches and fingering motion in the piano-score model improves the quality of reduction scores in high-difficulty cases.  ...  An iterative optimization algorithm for piano reduction is developed based on statistical inference of the model.  ...  Such a model for piano music with unknown hand parts can be constructed based on the merged-output HMM [18, 20] .  ... 
arXiv:1808.05006v2 fatcat:px2dnb3gpzff7e5ebdytk5v7bi

Statistical piano reduction controlling performance difficulty

Eita Nakamura, Kazuyoshi Yoshii
2018 APSIPA Transactions on Signal and Information Processing  
dependence of pitches and fingering motion in the piano-score model improves the quality of reduction scores in high-difficulty cases.  ...  An iterative optimization algorithm for piano reduction is developed based on statistical inference of the model.  ...  Such a model for piano music with unknown hand parts can be constructed based on the merged-output HMM [18, 20] .  ... 
doi:10.1017/atsip.2018.18 fatcat:h3ksiyvvufcctlrynvjhdnctvi

Music Information Processing for Visualization with Musical Notations

Satoru FUKAYAMA
2020 Transactions of Visualization Society of Japan  
Uitdenbogerd, D. and Zobel, J.: Melodic Matching Techniques for Large Music Databases, , pp.57-66 (1999). 11) Nakamura, E., Ono, N. and Sagayama, S.: Merged-output HMM for Piano Fingering of Both Hands  ...  E-mail:s.fukayama@aist.go.jp 〒 305-8568 茨城県つくば市梅園 1-1-1 中央第 2 と 周 辺 の コ ン テ キ ス ト に 応 じ て 各 音 の MIDI velocity を推定する研究が行われている 12) え ば,マ ー チ(行 進 曲)の 楽 譜 に お い る 手 法 が 有 用 で あ る.例 と し て は GenerativeTheory of  ... 
doi:10.3154/jvs.40.158_19 fatcat:ijyhvqhnrbd6rmt62ddxgpstlu

Detecting Hands from Piano MIDI Data

Aristotelis Hadjakos, Simon Waloschek, Alexander Leemhuis
2019 Mensch & Computer  
With the help of a Recurrent Neural Network (RNN), we assign played MIDI notes to one of the two hands.  ...  When a pianist is playing on a MIDI keyboard, the computer does not know with which hand a key was pressed.  ...  To perform fingering prediciton, it is necessary to assign each note to one hand. Nakamura et al. [17] report the accuracy of predicting the accuracy of hand detection with their merged-output HMM.  ... 
doi:10.18420/muc2019-ws-578 dblp:conf/mc/HadjakosWL19 fatcat:hfkwbwyqyjg7tlhhuboeqylf6m

Estimation of playable piano fingering by pitch-difference fingering match model

Xin Guan, Haoyue Zhao, Qiang Li
2022 EURASIP Journal on Audio, Speech, and Music Processing  
Furthermore, the state transfer matrix of HMM often makes the fingering of notes in compact scales unplayable without moving the hands.  ...  AbstractMost existing statistical models used to predict piano fingering apply explicit constraints among fingers and between fingers and notes; however, they disregard the relationship among notes.  ...  Acknowledgements This work was supported partly by the Natural Science Foundation of Tianjin Municipal Science and Technology Commission (16JCZDJC31100) and National Natural Science Foundation of China  ... 
doi:10.1186/s13636-022-00237-8 fatcat:zkbmg2s4vrhizb46dbtcgrpjse

Minimax Viterbi Algorithm For Hmm-Based Guitar Fingering Decision

Hori, Shigeki Sagayama
2016 Zenodo  
[6] applied merged-output HMM to piano fingering decision. Comparing to those previous works, the present work is new in that it introduces "minimax paradigm" to automatic fingering decision.  ...  FINGERING DECISION BASED ON HMM We implement automatic fingering decision based on an HMM whose hidden states are left hand forms and output symbols are musical notes played by the left hand forms.  ... 
doi:10.5281/zenodo.1417639 fatcat:yye6vue5dja6fmtgsloqtwju6u

Estimation of Playable Piano Fingering by Pitch-difference Fingering Matching Model [article]

Haoyue Zhao and Xin Guan and Qiang Li
2021 arXiv   pre-print
and 1.6% respective-ly, and the fingering for all scores can be playable.  ...  The existing piano fingering labeling statistical models usually consider the constraints among the fingers and the correlation between fingering and notes, and rarely include the relationship among the  ...  [11] proposed a "merged HMM" to automatically separate and label the unseparated left-hand and right-hand fractions. Li Qiang et al.  ... 
arXiv:2108.09058v1 fatcat:6n4wd7zwpjcs3ozngzmmq6j6iu

Non-Local Musical Statistics as Guides for Audio-to-Score Piano Transcription [article]

Kentaro Shibata, Eita Nakamura, Kazuyoshi Yoshii
2021 arXiv   pre-print
The integrated method had an overall transcription error rate of 7.1% and a downbeat F-measure of 85.6% on a dataset of popular piano music, and the generated transcriptions can be partially used for music  ...  We found that these statistics are markedly effective for improving the transcription results and that their optimal combination includes statistics obtained from separated hand parts.  ...  Andrew McLeod for useful discussions and a careful reading of the preliminary version of the manuscript.  ... 
arXiv:2008.12710v2 fatcat:yvtzt274pncj3gqeebb4sabeom

New Interfaces and Approaches to Machine Learning When Classifying Gestures within Music

Chris Rhodes, Richard Allmendinger, Ricardo Climent
2020 Entropy  
Thus, we used Wekinator and the Myo armband GI and study three performance gestures for piano practice to solve this problem.  ...  In recent years, machine learning (ML) has been important for the artform.  ...  Our many thanks also to Katherine Bosworth and Gustavo Góngora Goloubintseff for their kind support when realising this project. Conflicts of Interest: The authors declare no conflict of interest.  ... 
doi:10.3390/e22121384 pmid:33297582 pmcid:PMC7762429 fatcat:6qyiwqwk4zejld7iadhja5eysu

Multimodal music information processing and retrieval: survey and future challenges [article]

Federico Simonetta, Stavros Ntalampiras, Federico Avanzini
2019 arXiv   pre-print
Towards improving the performance in various music information processing tasks, recent studies exploit different modalities able to capture diverse aspects of music.  ...  Subsequently, we analyze existing information fusion approaches, and we conclude with the set of challenges that Music Information Retrieval and Sound and Music Computing research communities should focus  ...  Object tracking has been also used to detect hand movements, for example in piano-tutoring applications.  ... 
arXiv:1902.05347v1 fatcat:i2indkxk3vcmxajn6ajkh56wva

Hand Gesture Recognition Based on Computer Vision: A Review of Techniques

Munir Oudah, Ali Al-Naji, Javaan Chahl
2020 Journal of Imaging  
This paper is a thorough general overview of hand gesture methods with a brief discussion of some possible applications.  ...  In addition, it tabulates the performance of these methods, focusing on computer vision techniques that deal with the similarity and difference points, technique of hand segmentation used, classification  ...  Conflicts of Interest: The authors of this manuscript have no conflicts of interest relevant to this work.  ... 
doi:10.3390/jimaging6080073 pmid:34460688 fatcat:zmid23k67vbozb54sfji4nlfiy

State of the Art in Hand and Finger Modeling and Animation

Nkenge Wheatland, Yingying Wang, Huaguang Song, Michael Neff, Victor Zordan, Sophie Jörg
2015 Computer graphics forum (Print)  
This state of the art report presents a review of the research in the area of hand and finger modeling and animation.  ...  Starting with the biological structure of the hand and its implications for how the hand moves, we discuss current methods in motion capturing hands, data-driven and physics-based algorithms to synthesize  ...  Piano playing involves both hands simultaneously playing 09] present a system using motion capture data to generate animated piano playing from MIDI files or musical scores.  ... 
doi:10.1111/cgf.12595 fatcat:eloaimqxgvhepow34uqg5cko4y

Music Interpretation Analysis. A Multimodal Approach To Score-Informed Resynthesis of Piano Recordings [article]

Federico Simonetta
2022 arXiv   pre-print
This Thesis discusses the development of technologies for the automatic resynthesis of music recordings using digital synthesizers.  ...  Second, the Thesis describes further works aiming at the democratization of music production tools via automatic resynthesis: 1) it elaborates software and file formats for historical music archiving and  ...  Acknowledgments 1,2 Not many thanks should be given for this work.  ... 
arXiv:2205.00941v1 fatcat:nnbfvywdyjgtfcapfq4nn2c3bq
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