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This paper considers the alignment of permutation for underdetermined blind source separation of convolutively mixed sparse signals in the frequency domain. To resolve the permutation ambiguities between the sources of neighbor frequency bins, a probabilistic approach based on maximizing a posteriori (MAP) is proposed. The prior distribution of the sources is assumed to follow a dependent multivariate...
This paper considers the estimation of time difference of arrival (TDOA) of multiple sparse sources when the number of sources is larger than that of the microphones. White Gaussian noise is assumed present at the microphone in addition to the instantaneously mixed sources. The TDOA estimate is obtained based on a maximum likelihood (ML) criteria, and the likelihood is obtained by marginalizing the...
This paper considers blind speech separation and recognition for human robot interaction in reverberant environment. In the proposed system, the speech sources whose number is more than the number of mixtures are separated by MMSE-criteria and recognized by HMM-based speech recognizer. Experimental result shows the superiority of the proposed system.
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