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Binary Sparse Coding of Convolutive Mixtures for Sound Localization and Separation via Spatialization
2016
IEEE Transactions on Signal Processing
We propose a sparse coding approach to address the problem of source-sensor localization and speech reconstruction. This approach relies on designing a dictionary of spatialized signals by projecting the microphone array recordings into the array manifolds characterized for different locations in a reverberant enclosure using the image model. Sparse representation over this dictionary enables identifying the subspace of the actual recordings and its correspondence to the source and sensor
doi:10.1109/tsp.2015.2488598
fatcat:jzgttdzfwja2fk53wbnq4uc65u