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A common approach to multiple Direction-of-Arrival (DOA) estimation of speech sources is to identify Time-Frequency (TF) bins with dominant Single Source (SS) and apply DOA estimation such as Multiple Signal Classification (MUSIC) only on those TF bins. In the state-of-the-art Direct Path Dominance (DPD)-MUSIC, the covariance matrix, used as the input to MUSIC, is calculated using only the TF bins...
Direction of arrival algorithms which exploit the eigenstructure of the spatial covariance matrix (such as MUSIC) encounter difficulties in the presence of strongly correlated sources. Since the broadband polynomial MUSIC is an extension of the narrowband version, it is unsurprising that the same issues arise. In this paper, we extend the spatial smoothing technique to broadband scenarios via spatially...
In the last decade, modified subspace DoA estimation methods such as G-MUSIC have been proposed, in the context where the number of available snapshots N is of the same order of magnitude than the number of sensors M. In this context, the conventional MUSIC algorithm fails in presence of close sources because the empirical covariance matrix is a poor estimate of the true covariance matrix. The G-MUSIC...
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