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Melody Track Selection Using Discriminative Language Model

Xiao WU, Ming LI, Hongbin SUO, Yonghong YAN

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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

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