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EnglishA weighted minimum variance distortionless response (WMVDR) algorithm for near-field sound localization in a reverberant environment is presented. The steered response power computation of the WMVDR is based on a machine learning component which improves the incoherent frequency fusion of the narrowband power maps. A support vector machine (SVM) classifier is adopted to select the components of the fusion. The skewness measure of the narrowband power map marginal distribution is showed to be an effective feature for the supervised learning of the power map selection. Experiments with both simulated and real data demonstrate the improvement of the WMVDR beamformer localization accuracy with respect to other state-of-the-art techniques.
| Titolo: | A weighted MVDR beamformer based on SVM learning for sound source localization | |
| Autori: | ||
| Data di pubblicazione: | 2016 | |
| Rivista: | ||
| Abstract: | A weighted minimum variance distortionless response (WMVDR) algorithm for near-field sound localization in a reverberant environment is presented. The steered response power computation of the WMVDR is based on a machine learning component which improves the incoherent frequency fusion of the narrowband power maps. A support vector machine (SVM) classifier is adopted to select the components of the fusion. The skewness measure of the narrowband power map marginal distribution is showed to be an effective feature for the supervised learning of the power map selection. Experiments with both simulated and real data demonstrate the improvement of the WMVDR beamformer localization accuracy with respect to other state-of-the-art techniques. | |
| Handle: | http://hdl.handle.net/11390/1086761 | |
| Appare nelle tipologie: | 1.1 Articolo in rivista |
File in questo prodotto:
| File | Descrizione | Tipologia | Licenza | |
|---|---|---|---|---|
| A weighted MVDR beamformer based on SVM learning for sound source localization.pdf | Articolo principale | Documento in Pre-print | Non pubblico | Accesso ristretto Richiedi una copia |
| Elsevier_PRL1-s2.0-S0167865516301659-main.pdf | Versione Editoriale (PDF) | Non pubblico | Accesso ristretto Richiedi una copia | |
| AWeightedMVDR_Elsevier_PrePrint.pdf | Documento in Pre-print |  | Open Access Visualizza/Apri |
http://hdl.handle.net/11390/1086761
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