@inproceedings{2f9c3e80046b4d32a465e015e54f8b69,
title = "Supervised source localization using diffusion kernels",
abstract = "Recently, we introduced a method to recover the controlling parameters of linear systems using diffusion kernels. In this paper, we apply our approach to the problem of source localization in a reverberant room using measurements from a single microphone. Prior recordings of signals from various known locations in the room are required for training and calibration. The proposed algorithm relies on a computation of a diffusion kernel with a specially-tailored distance measure. Experimental results in a real reverberant environment demonstrate accurate recovery of the source location.",
keywords = "Source localization, acoustic localization, diffusion geometry, diffusion kernel, manifold learning",
author = "Ronen Talmon and Israel Cohen and Sharon Gannot",
year = "2011",
doi = "10.1109/ASPAA.2011.6082267",
language = "الإنجليزيّة",
isbn = "9781457706912",
series = "IEEE Workshop on Applications of Signal Processing to Audio and Acoustics",
pages = "245--248",
booktitle = "2011 IEEE Workshop on Applications of Signal Processing to Audio and Acoustics, WASPAA 2011",
note = "2011 IEEE Workshop on Applications of Signal Processing to Audio and Acoustics, WASPAA 2011 ; Conference date: 16-10-2011 Through 19-10-2011",
}