IEICE TRANSACTIONS on Information
Melody Track Selection Using Discriminative Language Model
Summary :
In this letter we focus on the task of selecting the melody track from a polyphonic MIDI file. Based on the intuition that music and language are similar in many aspects, we solve the selection problem by introducing an n-gram language model to learn the melody co-occurrence patterns in a statistical manner and determine the melodic degree of a given MIDI track. Furthermore, we propose the idea of using background model and posterior probability criteria to make modeling more discriminative. In the evaluation, the achieved 81.6% correct rate indicates the feasibility of our approach.
- Publication
- IEICE TRANSACTIONS on Information Vol.E91-D No.6 pp.1838-1840
- Publication Date
- 2008/06/01
- Publicized
- Online ISSN
- 1745-1361
- DOI
- 10.1093/ietisy/e91-d.6.1838
- Type of Manuscript
- LETTER
- Category
- Music Information Processing
Authors
Keyword
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Xiao WU, Ming LI, Hongbin SUO, Yonghong YAN, "Melody Track Selection Using Discriminative Language Model" in IEICE TRANSACTIONS on Information,
vol. E91-D, no. 6, pp. 1838-1840, June 2008, doi: 10.1093/ietisy/e91-d.6.1838.
Abstract: In this letter we focus on the task of selecting the melody track from a polyphonic MIDI file. Based on the intuition that music and language are similar in many aspects, we solve the selection problem by introducing an n-gram language model to learn the melody co-occurrence patterns in a statistical manner and determine the melodic degree of a given MIDI track. Furthermore, we propose the idea of using background model and posterior probability criteria to make modeling more discriminative. In the evaluation, the achieved 81.6% correct rate indicates the feasibility of our approach.
URL: https://global.ieice.org/en_transactions/information/10.1093/ietisy/e91-d.6.1838/_p
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@ARTICLE{e91-d_6_1838,
author={Xiao WU, Ming LI, Hongbin SUO, Yonghong YAN, },
journal={IEICE TRANSACTIONS on Information},
title={Melody Track Selection Using Discriminative Language Model},
year={2008},
volume={E91-D},
number={6},
pages={1838-1840},
abstract={In this letter we focus on the task of selecting the melody track from a polyphonic MIDI file. Based on the intuition that music and language are similar in many aspects, we solve the selection problem by introducing an n-gram language model to learn the melody co-occurrence patterns in a statistical manner and determine the melodic degree of a given MIDI track. Furthermore, we propose the idea of using background model and posterior probability criteria to make modeling more discriminative. In the evaluation, the achieved 81.6% correct rate indicates the feasibility of our approach.},
keywords={},
doi={10.1093/ietisy/e91-d.6.1838},
ISSN={1745-1361},
month={June},}
Copy
TY - JOUR
TI - Melody Track Selection Using Discriminative Language Model
T2 - IEICE TRANSACTIONS on Information
SP - 1838
EP - 1840
AU - Xiao WU
AU - Ming LI
AU - Hongbin SUO
AU - Yonghong YAN
PY - 2008
DO - 10.1093/ietisy/e91-d.6.1838
JO - IEICE TRANSACTIONS on Information
SN - 1745-1361
VL - E91-D
IS - 6
JA - IEICE TRANSACTIONS on Information
Y1 - June 2008
AB - In this letter we focus on the task of selecting the melody track from a polyphonic MIDI file. Based on the intuition that music and language are similar in many aspects, we solve the selection problem by introducing an n-gram language model to learn the melody co-occurrence patterns in a statistical manner and determine the melodic degree of a given MIDI track. Furthermore, we propose the idea of using background model and posterior probability criteria to make modeling more discriminative. In the evaluation, the achieved 81.6% correct rate indicates the feasibility of our approach.
ER -
English
