Joint acoustic localization and dereverberation through plane wave decomposition and sparse regularization
| Type of publication: | Journal paper |
| Citation: | Antonello_TASLP-2_2019 |
| Publication status: | Accepted |
| Journal: | IEEE/ACM Transactions on Audio, Speech, and Language Processing |
| Volume: | 27 |
| Number: | 12 |
| Year: | 2019 |
| Month: | December |
| Pages: | 1893-1905 |
| URL: | https://ieeexplore.ieee.org/do... |
| 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. |
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| Added by: | [UNK] |
| Total mark: | 0 |
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