Melody Track Selection Using Discriminative Language Model
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概要
- 論文の詳細を見る
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.
- （社）電子情報通信学会の論文
- 2008-06-01
著者
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Yan Yonghong
Thinkit Speech Lab. Institute Of Acoustics Chinese Academy Of Sciences
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Yan Yonghong
Institute Of Acoustics Chinese Academy Of Science
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SUO Hongbin
ThinkIT Speech Lab., Institute of Acoustics, Chinese Academy of Sciences
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Yan Yonghong
Thinkit Speech Lab Institute Of Acoustics Chinese Academy Of Sciences
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Yan Yonghong
Thinkit Speech Lab.
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Yan Yonghong
Thinkit Speech Laboratory Institute Of Acoustics Chinese Academy Of Sciences Beijing
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LI Ming
ThinkIT Speech Lab., Institute of Acoustics, Chinese Academy of Sciences
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WU Xiao
ThinkIT Speech Lab., Institute of Acoustics, Chinese Academy of Sciences
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Li Ming
Thinkit Speech Lab. Institute Of Acoustics Chinese Academy Of Sciences
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Wu Xiao
Thinkit Speech Lab. Institute Of Acoustics Chinese Academy Of Sciences
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Suo Hongbin
Thinkit Speech Lab Institute Of Acoustics Chinese Academy Of Sciences
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