Structure Learning and Source Separation of Music Audio Signals based on Bayesian Nonparametrics
| Project/Area Number |
23700184
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| Research Category |
Grant-in-Aid for Young Scientists (B)
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| Allocation Type | Multi-year Fund |
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| Research Field |
Intelligent informatics
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| Research Institution | National Institute of Advanced Industrial Science and Technology |
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Principal Investigator |
YOSHII Kazuyoshi 独立行政法人産業技術総合研究所, 情報技術研究部門, 主任研究員 (20510001)
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| Project Period (FY) |
2011 – 2012
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| Project Status |
Completed (Fiscal Year 2012)
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| Budget Amount *help |
¥4,420,000 (Direct Cost: ¥3,400,000、Indirect Cost: ¥1,020,000)
Fiscal Year 2012: ¥1,170,000 (Direct Cost: ¥900,000、Indirect Cost: ¥270,000)
Fiscal Year 2011: ¥3,250,000 (Direct Cost: ¥2,500,000、Indirect Cost: ¥750,000)
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| Keywords | 音楽情報処理 / 機械学習 / ノンパラメトリックベイズ |
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| Research Abstract |
This research aims to develop a nonparametric Bayesian model that can be used for jointly performing source separation and structure learning of music audio signals in an unsupervised manner. First, we have studied on structure learning of music scores (s
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Report
(3 results)
Research Products
(23 results)
