The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. ex. Some numerals are expressed as "XNUMX".
Copyrights notice
The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. Copyrights notice
Makalah ini mencadangkan krogram yang menonjol dengan mengalih keluar aliran tempatan untuk meningkatkan ketepatan pengenalan lagu muka depan. Kromagram menonjol yang dicadangkan menekankan kandungan tonal muzik, yang dipelihara dengan baik antara lagu asal dan versi muka depannya, sambil mengurangkan kesan perbezaan kayu. Kami menggunakan kromagram menonjol yang dicadangkan pada pengenalan lagu muka depan berdasarkan penjajaran jujukan. Eksperimen pada dua set data lagu muka depan mengesahkan bahawa krogram menonjol yang dicadangkan meningkatkan ketepatan pengenalan lagu muka depan.
Jin S. SEO
Gangneung-Wonju National University
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Salinan
Jin S. SEO, "Salient Chromagram Extraction Based on Trend Removal for Cover Song Identification" in IEICE TRANSACTIONS on Information,
vol. E104-D, no. 1, pp. 51-54, January 2021, doi: 10.1587/transinf.2020MUL0002.
Abstract: This paper proposes a salient chromagram by removing local trend to improve cover song identification accuracy. The proposed salient chromagram emphasizes tonal contents of music, which are well-preserved between an original song and its cover version, while reducing the effects of timber difference. We apply the proposed salient chromagram to the sequence-alignment based cover song identification. Experiments on two cover song datasets confirm that the proposed salient chromagram improves the cover song identification accuracy.
URL: https://global.ieice.org/en_transactions/information/10.1587/transinf.2020MUL0002/_p
Salinan
@ARTICLE{e104-d_1_51,
author={Jin S. SEO, },
journal={IEICE TRANSACTIONS on Information},
title={Salient Chromagram Extraction Based on Trend Removal for Cover Song Identification},
year={2021},
volume={E104-D},
number={1},
pages={51-54},
abstract={This paper proposes a salient chromagram by removing local trend to improve cover song identification accuracy. The proposed salient chromagram emphasizes tonal contents of music, which are well-preserved between an original song and its cover version, while reducing the effects of timber difference. We apply the proposed salient chromagram to the sequence-alignment based cover song identification. Experiments on two cover song datasets confirm that the proposed salient chromagram improves the cover song identification accuracy.},
keywords={},
doi={10.1587/transinf.2020MUL0002},
ISSN={1745-1361},
month={January},}
Salinan
TY - JOUR
TI - Salient Chromagram Extraction Based on Trend Removal for Cover Song Identification
T2 - IEICE TRANSACTIONS on Information
SP - 51
EP - 54
AU - Jin S. SEO
PY - 2021
DO - 10.1587/transinf.2020MUL0002
JO - IEICE TRANSACTIONS on Information
SN - 1745-1361
VL - E104-D
IS - 1
JA - IEICE TRANSACTIONS on Information
Y1 - January 2021
AB - This paper proposes a salient chromagram by removing local trend to improve cover song identification accuracy. The proposed salient chromagram emphasizes tonal contents of music, which are well-preserved between an original song and its cover version, while reducing the effects of timber difference. We apply the proposed salient chromagram to the sequence-alignment based cover song identification. Experiments on two cover song datasets confirm that the proposed salient chromagram improves the cover song identification accuracy.
ER -