• Title/Summary/Keyword: Under-determined blind source separation

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Implementation of Blind Source Recovery Using the Gini Coefficient (Gini 계수를 이용한 Blind Source Recovery 방법의 구현)

  • Jeong, Jae-Woong;Song, Eun-Jung;Park, Young-Cheol;Youn, Dae-Hee
    • The Journal of the Acoustical Society of Korea
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    • v.27 no.1
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    • pp.26-32
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    • 2008
  • UBSS (unde-determined blind source separation) is composed of the stages of BMMR (blind mixing matrix recovery) and BSR (blind source recovery). Generally, these two stages are executed using the sparseness of the observed data, and their performance is influenced by the accuracy of the measure of the sparseness. In this paper, as introducing the measure of the sparseness using the Gini coefficient to BSR stage, we obtained more accurate measure of the sparseness and better performance of BSR than methods using the $l_1$-norm, $l_q$-norm, and hyperbolic tangent, which was confirmed via computer simulations.

Blind Rhythmic Source Separation (블라인드 방식의 리듬 음원 분리)

  • Kim, Min-Je;Yoo, Ji-Ho;Kang, Kyeong-Ok;Choi, Seung-Jin
    • The Journal of the Acoustical Society of Korea
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    • v.28 no.8
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    • pp.697-705
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    • 2009
  • An unsupervised (blind) method is proposed aiming at extracting rhythmic sources from commercial polyphonic music whose number of channels is limited to one. Commercial music signals are not usually provided with more than two channels while they often contain multiple instruments including singing voice. Therefore, instead of using conventional modeling of mixing environments or statistical characteristics, we should introduce other source-specific characteristics for separating or extracting sources in the under determined environments. In this paper, we concentrate on extracting rhythmic sources from the mixture with the other harmonic sources. An extension of nonnegative matrix factorization (NMF), which is called nonnegative matrix partial co-factorization (NMPCF), is used to analyze multiple relationships between spectral and temporal properties in the given input matrices. Moreover, temporal repeatability of the rhythmic sound sources is implicated as a common rhythmic property among segments of an input mixture signal. The proposed method shows acceptable, but not superior separation quality to referred prior knowledge-based drum source separation systems, but it has better applicability due to its blind manner in separation, for example, when there is no prior information or the target rhythmic source is irregular.