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A Timbre-based Approach to Estimate Key Velocity from Polyphonic Piano Recordings
2018
Zenodo
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Estimating the key velocity of each note from polyphonic piano music is a highly challenging task. Previous work addressed the problem by estimating note intensity using a polyphonic note model. ...
Combining the note intensity from the separated notes with the statistics of the neural network prediction, the proposed method estimates the key velocity in the dimension of MIDI note velocity. ...
ACKNOWLEDGEMENTS This research was supported/partially supported by Samsung Research Funding & Incubation Center for Future Research. ...
doi:10.5281/zenodo.1492359
fatcat:rvoqsw6a2vdzfheqgppvmvlmkm
Score-Informed Source Separation for Music Signals
2012
Dagstuhl Publications
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In particular, additional note information as specified by a musical score or a MIDI file has been employed to support various audio processing tasks such as source separation, audio parameterization, ...
In recent years, the processing of audio recordings by exploiting additional musical knowledge has turned out to be a promising research direction. ...
In a final step, the individual note intensities are estimated using the adapted note-event spectrograms described by the model. ...
doi:10.4230/dfu.vol3.11041.73
dblp:conf/dagstuhl/EwertM12
fatcat:eobsimoinjf5vcnpg4leewbctm
An Assessment of Learned Score Features for Modeling Expressive Dynamics in Music
2014
IEEE transactions on multimedia
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The purpose of this paper is to evaluate the utility of unsupervised feature learning in the context of modeling expressive dynamics, in particular note intensities of performed music. ...
The experiments are done using a data set comprising professional performances of Chopin's complete piano repertoire. ...
in note intensity is explained by the models. ...
doi:10.1109/tmm.2014.2311013
fatcat:quo5uwabdrcblltoqiimtlvoii
Semi-Supervised Convolutive NMF for Automatic Piano Transcription
[article]
2022
arXiv
pre-print
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In the semi-supervised setting, only a single recording of each individual notes is required. ...
Automatic Music Transcription, which consists in transforming an audio recording of a musical performance into symbolic format, remains a difficult Music Information Retrieval task. ...
Other works have also considered enriching NMF with several templates per note albeit not using convolution, typically by fusing rows of the estimated H matrix a posteriori [13] [14] [15] . ...
arXiv:2202.04989v2
fatcat:iatxmebsfrdkplzqdpoa73tqpi
Automatic music transcription: challenges and future directions
2013
Journal of Intelligent Information Systems
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Other promising approaches include the integration of information from multiple algorithms and different musical aspects. ...
J Intell Inf Syst audio data now available are a rich potential source of training data, via forced alignment of audio to scores, but large scale utilisation of such data has yet to be attempted. ...
As far as dynamics are concerned, in Ewert and Müller (2011) a method was proposed for estimating note intensities in a score-informed scenario. ...
doi:10.1007/s10844-013-0258-3
fatcat:olfkl6jj7jhl3nxcy6td6qgdj4
Automatic Music Transcription: Breaking The Glass Ceiling
2012
Zenodo
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As far as dynamics are concerned, in [15] a method was proposed for estimating note intensities in a score-informed scenario. ...
[38] ), which automatically contain intensity information such as MIDI note velocities. ...
doi:10.5281/zenodo.1415088
fatcat:rfrzyhmfebaanppofxfcbxgei4
Score-Informed Identification Of Missing And Extra Notes In Piano Recordings
2016
Zenodo
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Acknowledgements: This work was partly funded by EP-SRC grant EP/L019981/1. ...
Sandler acknowledges the support of the Royal Society as a recipient of a Wolfson Research Merit Award. ...
"Score-Informed Identification of Missing and Extra Notes in Piano Recordings", 17th International Society for Music Information Retrieval Conference, 2016. ...
doi:10.5281/zenodo.1418317
fatcat:gqr2iifkzzgu5owcgo53ghtfnm
A Study on Separation Method Combined Gamma-Process Non-negative Matrix Factorization and Deep Learning
2019
Proceedings of the ICA congress
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The basis estimated by GaP-NMF is emphasized by multiplying with the spectrum template of musical instruments which is specified by DNN. ...
In the proposed method, we first estimate the basis with GaP-NMF. Then, DNN classifies the estimated basis according to musical instruments. ...
The basis matrix which is estimated by GaP -NMF is not a set of the spectrum of a single tone. ...
doi:10.18154/rwth-conv-239719
fatcat:lxxb646wzrbdlhmm5xoitjpq3y
Identifying Missing and Extra Notes in Piano Recordings Using Score-Informed Dictionary Learning
2017
IEEE/ACM Transactions on Audio Speech and Language Processing
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By adapting a scoreinformed dictionary learning technique as used for source separation, we learn for each score pitch a spectral pattern describing the energy distribution of associated notes in the recording ...
The goal of automatic music transcription (AMT) is to obtain a high-level symbolic representation of the notes played in a given audio recording. ...
CONCLUSION In this paper, we introduce a score-informed transcription method to identify missing and extra notes in piano recordings. ...
doi:10.1109/taslp.2017.2724203
fatcat:mpc7nybh4rgmzhkpzlujwyxxp4
Evaluation of the Convolutional NMF for Supervised Polyphonic Music Transcription and Note Isolation
[chapter]
2015
Lecture Notes in Computer Science
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We evaluate the convolutive nonnegative matrix factorization in the context of automatic music transcription of polyphonic piano recordings and the associated problem of note isolation. ...
Our intention is to find out whether the temporal continuity of piano notes is truthfully captured by the convolutional kernels and how the performance scales with complexity. ...
separate note recordings. ...
doi:10.1007/978-3-319-22482-4_51
fatcat:nay6iplm7nalhky6h7gtdvmvsm
Onsets and Frames: Dual-Objective Piano Transcription
[article]
2018
arXiv
pre-print
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We advance the state of the art in polyphonic piano music transcription by using a deep convolutional and recurrent neural network which is trained to jointly predict onsets and frames. ...
Our approach results in over a 100% relative improvement in note F1 score (with offsets) on the MAPS dataset. ...
While various studies have considered the estimation of dynamics (note intensities or velocities) in a recording given the score [10, 22, 26] , to our knowledge there has been no work in the literature ...
arXiv:1710.11153v2
fatcat:pc7zcl337bd3linf3bevkwi4je
Onsets and Frames: Dual-Objective Piano Transcription
2018
Zenodo
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We advance the state of the art in polyphonic piano music transcription by using a deep convolutional and recurrent neural network which is trained to jointly predict onsets and frames. ...
Our approach results in over a 100% relative improvement in note F1 score (with offsets) on the MAPS dataset. ...
While various studies have considered the estimation of dynamics (note intensities or velocities) in a recording given the score [10, 22, 26] , to our knowledge there has been no work in the literature ...
doi:10.5281/zenodo.1492340
fatcat:beja2zsu4jgudbhkja4lhqb2qe
Generative Spectrogram Factorization Models for Polyphonic Piano Transcription
2010
IEEE Transactions on Audio, Speech, and Language Processing
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Index Terms-Frequency estimation, matrix decomposition, music information retrieval (MIR), spectral analysis, time-frequency analysis. 2 ...
The performance of the system is compared to that of existing discriminative and model-based approaches on a dataset of solo piano music. ...
This table Table II by splitting the test data into the recorded piano extracts and the MIDI synthesized extracts. ...
doi:10.1109/tasl.2009.2029769
fatcat:le6sa5kqyvfyxnciiu5rwdphya
Audio Source Separation Using Multiple Deformed References
2014
Zenodo
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Publication in the conference proceedings of EUSIPCO, Lisbon, Portugal, 2014 ...
For instance, text-informed separation [9] , score informed [6] , separation by humming [11] , cover guided separation [10] are some of them. ...
More recently, a number of approaches have been proposed to exploit information about the recording conditions, the musical score [6] , the fundamental frequency 0 [7] , the language model [8] , the ...
doi:10.5281/zenodo.43873
fatcat:vwljdj462bhgzeau72tjf6fxey
Generating Data To Train Convolutional Neural Networks For Classical Music Source Separation
2017
Proceedings of the SMC Conferences
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Acknowledgments The TITANX used for this research was donated by the Proceedings of the 14th Sound and Music Computing Conference, July 5-8, Espoo, Finland SMC2017-232 ...
Although successful, informed NMF approaches are computationally intensive, which makes them difficult to use in a low latency scenario. ...
Because we deal with a score-constrained scenario and for a fair comparison, the gains of the NMF are restricted to the notes in the score, without taking into account the time when the notes are played ...
doi:10.5281/zenodo.1401922
fatcat:z4bq6dksynhodglcsybhby34iu
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