Sparse Sinusoidal Representation for Monaural Sound Separation
Publish place: 16th Iranian Conference on Electric Engineering
Publish Year: 1387
Type: Conference paper
Language: English
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Document National Code:
ICEE16_114
Index date: 25 February 2008
Sparse Sinusoidal Representation for Monaural Sound Separation abstract
We present a Fixed Dimension Modified Sinusoid Model (FD-MSM) for parametric analysis of all audible signals consisting of speech, music and their mixtures. Compared with previous analysis models, the proposed scheme is pitch independent as well as appropriate for commonly used clustering algorithms including Vector Quantization (VQ) or Gaussian Mixture Model (GMM) due to its fixed feature dimension which in turn results in a significant reduction in search space. Evaluating proposed FD-MSM by conducting subjective experiments, we observed that the resulting signal is perceptually indistinguishable from the original.
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Sparse Sinusoidal Representation for Monaural Sound Separation authors
Pejman Mowlaee Begzade Mahale
Department of Electrical Engineering, Amirkabir University.
Abolghasem Sayadiyan
Department of Electrical Engineering, Amirkabir University.
M Rahmati
Associate Professor at Computer Engineering Department
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