%Aigaion2 BibTeX export from Idiap Publications
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@ARTICLE{Antonello_TASLP-2_2019,
         author = {Antonello, Niccol{\`{o}} and De Sena, Enzo and Moonen, Marc and Naylor, A. Patrick and van Waterschoot, Toon},
       projects = {Idiap},
          month = dec,
          title = {Joint acoustic localization and dereverberation through plane wave decomposition and sparse regularization},
        journal = {IEEE/ACM Transactions on Audio, Speech, and Language Processing},
         volume = {27},
         number = {12},
           year = {2019},
          pages = {1893-1905},
            url = {https://ieeexplore.ieee.org/document/8788551},
            doi = {IEEE/ACM Transactions on Audio, Speech, and Language Processing},
       abstract = {Acoustic source localization and dereverberation are formulated jointly as an inverse problem. The inverse problem consists of the approximation of the sound field measured by a set of microphones. The recorded sound pressure is matched with that of a particular acoustic model based on a collection of plane waves arriving from different directions at the microphone positions. In order to achieve meaningful results, spatial and spatio-spectral sparsity can be promoted in the weight signals controlling the plane waves. The large-scale optimization problem resulting from the inverse problem formulation is solved using a first order optimization algorithm combined with a weighted overlap-add procedure. It is shown that once the weight signals capable of effectively approximating the sound field are obtained, they can be readily used to localize a moving sound source in terms of direction of arrival (DOA) and to perform dereverberation in a highly reverberant environment. Results from simulation experiments and from real measurements show that the proposed algorithm is robust against both localized and diffuse noise exhibiting a noise reduction in the dereverberated signals.},
            pdf = {https://publications.idiap.ch/attachments/papers/2019/Antonello_TASLP-2_2019.pdf}
}