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Rhythm Transcription of Polyphonic Piano Music Based on Merged-Output HMM for Multiple Voices [article]

Eita Nakamura, Kazuyoshi Yoshii, Shigeki Sagayama
2017 arXiv   pre-print
In a recent conference paper, we have reported a rhythm transcription method based on a merged-output hidden Markov model (HMM) that explicitly describes the multiple-voice structure of polyphonic music  ...  In this paper we present a complete description of the proposed model and develop an inference technique, which is valid for any merged-output HMMs for which output probabilities depend on past events.  ...  The author EN thanks Hiroaki Tanaka for useful discussions on mergedoutput HMM and Yoshiaki Bando for his help with running computer programs.  ... 
arXiv:1701.08343v1 fatcat:xf6dnigtwbcm7mrdpt5jvq77ii

Rhythm Transcription Of Polyphonic Midi Performances Based On A Merged-Output Hmm For Multiple Voices

Eita Nakamura, Kazuyoshi Yoshii, Shigeki Sagayama
2016 Proceedings of the SMC Conferences  
Merged-Output HMM Recently merged-output HMM has been proposed as an HMM-based model for describing symbolic signals of polyphonic music with multiple voices.  ...  The situation calls for a similar treatment of multiple voices for polyphonic rhythm transcription.  ... 
doi:10.5281/zenodo.851275 fatcat:i5qya4qhtvggvkxmvsoryoc5fi

Note Value Recognition for Piano Transcription Using Markov Random Fields

Eita Nakamura, Kazuyoshi Yoshii, Simon Dixon
2017 IEEE/ACM Transactions on Audio Speech and Language Processing  
This paper presents a statistical method for use in music transcription that can estimate score times of note onsets and offsets from polyphonic MIDI performance signals.  ...  could only output incomplete musical scores.  ...  ACKNOWLEDGEMENT We are grateful to David Temperley for providing source code for the Melisma Analyzer. E.  ... 
doi:10.1109/taslp.2017.2722103 fatcat:2q4gekbw3nd3hphzvmba6pko2a

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 present an automatic piano transcription system that converts polyphonic audio recordings into musical scores.  ...  Andrew McLeod for useful discussions and a careful reading of the preliminary version of the manuscript.  ... 
arXiv:2008.12710v2 fatcat:yvtzt274pncj3gqeebb4sabeom

A Holistic Approach to Polyphonic Music Transcription with Neural Networks

Miguel Roman, Antonio Pertusa, Jorge Calvo-Zaragoza
2019 Zenodo  
The output is a textual representation of four-voice music scores based on **kern format.  ...  We present a framework based on neural networks to extract music scores directly from polyphonic audio in an end-to-end fashion.  ...  errors from one stage to the other; 3) The output of our model is based on **kern format and can be straightforwardly translated to a valid music score.  ... 
doi:10.5281/zenodo.3527914 fatcat:otrre7szwnfl7hifsbdee25ree

A holistic approach to polyphonic music transcription with neural networks [article]

Miguel A. Román, Antonio Pertusa, Jorge Calvo-Zaragoza
2019 arXiv   pre-print
The output is a textual representation of four-voice music scores based on **kern format.  ...  We present a framework based on neural networks to extract music scores directly from polyphonic audio in an end-to-end fashion.  ...  errors from one stage to the other; 3) The output of our model is based on **kern format and can be straightforwardly translated to a valid music score.  ... 
arXiv:1910.12086v1 fatcat:utyjaa4zhzgprfefcnv77x6tae

A Comprehensive Survey on Deep Music Generation: Multi-level Representations, Algorithms, Evaluations, and Future Directions [article]

Shulei Ji, Jing Luo, Xinyu Yang
2020 arXiv   pre-print
Especially music, the topic of this paper, has attracted widespread attention of countless researchers.The whole process of producing music can be divided into three stages, corresponding to the three  ...  In addition, we summarize the datasets suitable for diverse tasks, discuss the music representations, the evaluation methods as well as the challenges under different levels, and finally point out several  ...  [242] used the neural network of music transcription based on encoder-decoder architecture to take a polyphonic music audio as input and predict its score as output, not only predicting the note pitch  ... 
arXiv:2011.06801v1 fatcat:cixou3d2jzertlcpb7kb5x5ery

Coupled Recurrent Models for Polyphonic Music Composition [article]

John Thickstun, Zaid Harchaoui, Dean P. Foster, Sham M. Kakade
2019 arXiv   pre-print
This paper introduces a novel recurrent model for music composition that is tailored to the structure of polyphonic music.  ...  We train models for single-voice and multi-voice composition on 2,300 scores from the KernScores dataset.  ...  For recent work on monophonic composition, see [13, 24, 27] . Work on polyphonic music composition is considerably more recent.  ... 
arXiv:1811.08045v2 fatcat:yxwmwf2mgfephiycwddarbuv7u

Evaluation Framework For Automatic Singing Transcription

Emilio Molina, Ana M. Barbancho, Lorenzo J. Tardón, Isabel Barbancho
2014 Zenodo  
We have used the method for automatic transcription of melody, bass line and chords in polyphonic music published by Ryynänen in 2008 [13] , although we only focus on melody transcription.  ...  One of the most representative HMM-based singing transcribers was published by Ryynänen in 2004 [9] .  ... 
doi:10.5281/zenodo.1417728 fatcat:lxi2kalpdfdfbjztjllhwnoc2q

Signal-to-Score Music Transcription using Graphical Models

Emir Kapanci, Avi Pfeffer
2005 International Joint Conference on Artificial Intelligence  
This paper focuses on the second stage, going from sound events to a notated score. We use a family of graphical models for this task.  ...  We present a transcription system that takes a music signal as input and returns its musical score. Two stages of processing are used.  ...  We have a style specific score prior P $ ¡ ¤£ ' , and a segmentation prior P $ ¡ £ ' based on the onset detector's outputs.  ... 
dblp:conf/ijcai/KapanciP05 fatcat:2w7dts5hbfdbdmok4363v6tmtm

Singing Phoneme Class Detection In Polyphonic Music Recordings

Ourania Vagia, Perfecto Herrera
2008 Zenodo  
Specifically, we are interested in building statistical classification models that are able to automatically distinguish sung consonants and vowels from pure instrumental music in polyphonic music recordings  ...  This thesis presents research into the problem of singing phoneme detection in polyphonic audio, in which the lyrics are in English.  ...  In (Nwe et al., 2004) the classification was done with multiple HMM models based on three parameters, the section type (intro, verse, chorus, bridge and outro), the tempo and the loudness.  ... 
doi:10.5281/zenodo.3744709 fatcat:bxl33cpakfevbeirbnq46xhtqe

Data-driven Pitch Content Description of Choral Singing Recordings

Helena Cuesta, Emilia Gómez
2022 Zenodo  
The second contribution is a set of deep learning models for multiple F0 estimation, streaming, and voice assignment of vocal quartets, mainly based on convolutional neural networks designed leveraging  ...  Then, we address three main research problems: multiple F0 estimation and streaming, voice assignment, and the characterization of vocal unisons, all in the context of four-part vocal ensembles.  ...  We wish for a bright future for research on choir music in the MIR field.  ... 
doi:10.5281/zenodo.6389643 fatcat:zibszrdivjhcnap2gzll3sbxga

Artificial Musical Intelligence: A Survey [article]

Elad Liebman, Peter Stone
2020 arXiv   pre-print
Beginning in the late 1990s, the rise of the Internet and large scale platforms for music recommendation and retrieval have made music an increasingly prevalent domain of machine learning and artificial  ...  its pursuit, with a particular emphasis on machine learning methods.  ...  For instance, McLeod and Steedman note in a recent paper, in the context of evaluating polyphonic music transcription, that "(i)t is less common to annotate this output with musical features such as voicing  ... 
arXiv:2006.10553v1 fatcat:2j6i27wrsfawpgcr2unxdgngd4

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

Federico Simonetta
2022 arXiv   pre-print
First, the main issue is identified in the understanding of how Music Information Processing (MIP) methods can take into consideration the influence of the acoustic context on the music performance.  ...  This Thesis discusses the development of technologies for the automatic resynthesis of music recordings using digital synthesizers.  ...  Acknowledgments 1,2 Not many thanks should be given for this work.  ... 
arXiv:2205.00941v1 fatcat:nnbfvywdyjgtfcapfq4nn2c3bq

16th Sound and Music Computing Conference SMC 2019 (28–31 May 2019, Malaga, Spain)

Lorenzo J. Tardón, Isabel Barbancho, Ana M. Barbancho, Alberto Peinado, Stefania Serafin, Federico Avanzini
2019 Applied Sciences  
The SMC 2019 TOPICS OF INTEREST included a wide selection of topics related to acoustics, psychoacoustics, music, technology for music, audio analysis, musicology, sonification, music games, machine learning  ...  The First International Day of Women in Inclusive Engineering, Sound and Music Computing Research (WiSMC 2019) took place on 28 May 2019.  ...  Acknowledgments: The 16th Sound and Music Computing Conference (SMC 2019) was made possible thanks to the hard work of many people including the authors, the reviewers, all the members of the Conference  ... 
doi:10.3390/app9122492 fatcat:tcacoupffjewnpjhpw4oy7x6h4
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