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Estimation of the Matrix Rank of Harmonic Components of a Spectrogram in a Piano Music Signal Based on the Stein's Unbiased Risk Estimator and Median Filter
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Summary :
The estimation of the matrix rank of harmonic components of a music spectrogram provides some useful information, e.g., the determination of the number of basis vectors of the matrix-factorization-based algorithms, which is required for the automatic music transcription or in post-processing. In this work, we develop an algorithm based on Stein's unbiased risk estimator (SURE) algorithm with the matrix factorization model. The noise variance required for the SURE algorithm is estimated by suppressing the harmonic component via median filtering. An evaluation performed using the MIDI-aligned piano sounds (MAPS) database revealed an average estimation error of -0.26 (standard deviation: 4.4) for the proposed algorithm.
- Publication
- IEICE TRANSACTIONS on Information Vol.E102-D No.11 pp.2276-2279
- Publication Date
- 2019/11/01
- Publicized
- 2019/08/22
- Online ISSN
- 1745-1361
- DOI
- 10.1587/transinf.2019EDL8049
- Type of Manuscript
- LETTER
- Category
- Music Information Processing
Authors
Seokjin LEE
Kyungpook National University
Keyword
Latest Issue
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Seokjin LEE, "Estimation of the Matrix Rank of Harmonic Components of a Spectrogram in a Piano Music Signal Based on the Stein's Unbiased Risk Estimator and Median Filter" in IEICE TRANSACTIONS on Information,
vol. E102-D, no. 11, pp. 2276-2279, November 2019, doi: 10.1587/transinf.2019EDL8049.
Abstract: The estimation of the matrix rank of harmonic components of a music spectrogram provides some useful information, e.g., the determination of the number of basis vectors of the matrix-factorization-based algorithms, which is required for the automatic music transcription or in post-processing. In this work, we develop an algorithm based on Stein's unbiased risk estimator (SURE) algorithm with the matrix factorization model. The noise variance required for the SURE algorithm is estimated by suppressing the harmonic component via median filtering. An evaluation performed using the MIDI-aligned piano sounds (MAPS) database revealed an average estimation error of -0.26 (standard deviation: 4.4) for the proposed algorithm.
URL: https://global.ieice.org/en_transactions/information/10.1587/transinf.2019EDL8049/_p
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@ARTICLE{e102-d_11_2276,
author={Seokjin LEE, },
journal={IEICE TRANSACTIONS on Information},
title={Estimation of the Matrix Rank of Harmonic Components of a Spectrogram in a Piano Music Signal Based on the Stein's Unbiased Risk Estimator and Median Filter},
year={2019},
volume={E102-D},
number={11},
pages={2276-2279},
abstract={The estimation of the matrix rank of harmonic components of a music spectrogram provides some useful information, e.g., the determination of the number of basis vectors of the matrix-factorization-based algorithms, which is required for the automatic music transcription or in post-processing. In this work, we develop an algorithm based on Stein's unbiased risk estimator (SURE) algorithm with the matrix factorization model. The noise variance required for the SURE algorithm is estimated by suppressing the harmonic component via median filtering. An evaluation performed using the MIDI-aligned piano sounds (MAPS) database revealed an average estimation error of -0.26 (standard deviation: 4.4) for the proposed algorithm.},
keywords={},
doi={10.1587/transinf.2019EDL8049},
ISSN={1745-1361},
month={November},}
Copy
TY - JOUR
TI - Estimation of the Matrix Rank of Harmonic Components of a Spectrogram in a Piano Music Signal Based on the Stein's Unbiased Risk Estimator and Median Filter
T2 - IEICE TRANSACTIONS on Information
SP - 2276
EP - 2279
AU - Seokjin LEE
PY - 2019
DO - 10.1587/transinf.2019EDL8049
JO - IEICE TRANSACTIONS on Information
SN - 1745-1361
VL - E102-D
IS - 11
JA - IEICE TRANSACTIONS on Information
Y1 - November 2019
AB - The estimation of the matrix rank of harmonic components of a music spectrogram provides some useful information, e.g., the determination of the number of basis vectors of the matrix-factorization-based algorithms, which is required for the automatic music transcription or in post-processing. In this work, we develop an algorithm based on Stein's unbiased risk estimator (SURE) algorithm with the matrix factorization model. The noise variance required for the SURE algorithm is estimated by suppressing the harmonic component via median filtering. An evaluation performed using the MIDI-aligned piano sounds (MAPS) database revealed an average estimation error of -0.26 (standard deviation: 4.4) for the proposed algorithm.
ER -
English
