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- W2384730619 abstract "A new blind source separation algorithm for convolved mixtures of speech singals is developed with consideration of different delayed multi-path reflections.Based on the sparseness property of speech signals,the proposed algorithm extracted time-delay and amplitude coefficient candidates through the contrast analysis of two speech spectrograms.Motivated by maximum likelihood estimation,we defined a reliablility function constructed from the parameter candidates.The reliability analysis histogram was shown to have one peak for each pair of parameters with peak location corresponding to the real time-delay and amplitude coefficient.Instead of using the independent assumption,the proposed algorithm made use of speech spectral sparseness to perform separation and proved to be applicable in most occasions.Since it involves no iterations and does not have the convergence problem,the proposed algorithm is fast and stable.Simulations and real-world experiments demonstrate the proposed method can accurately estimate time-delays and amplitude coefficients in various SNR conditions.Successful recovery of source signals using estimated parameters proves algorithm feasible and can be applied to real-world speech separation applications." @default.
- W2384730619 created "2016-06-24" @default.
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- W2384730619 date "2006-01-01" @default.
- W2384730619 modified "2023-09-24" @default.
- W2384730619 title "A Time-Frequency Analysis Based Blind Source Deconvolution Method" @default.
- W2384730619 hasPublicationYear "2006" @default.
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