@inproceedings{e0d797cea24b430fbb40418d524bbe82,
title = "Learning-Based Acoustic Source Localization Using Directional Spectra",
abstract = "This paper proposes to use directional spectra as new features for manifold-learning-based acoustic source localization. We claim that directional spectra not only contain directional information, but are rather discriminative for different positions in a reverberant enclosure. We use these proposed features to build a manifold-learning-based localization algorithm which is applied to single-array localization as well as to Acoustic Sensor Network (ASN) localization. The performance of the proposed algorithm is benchmarked by comprehensive experiments carried out in a simulated environment, with comparison to a blind approach based on triangulation, as well as by Gaussian Process Regression (GPR)-based localization.",
keywords = "Gaussian Process Regression, Manifold Learning, SRP-PHAT",
author = "Andreas Brendel and Bracha Laufer-Goldshtein and Sharon Gannot and Walter Kellermann",
note = "Publisher Copyright: {\textcopyright} 2019 IEEE.; 8th IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing, CAMSAP 2019 ; Conference date: 15-12-2019 Through 18-12-2019",
year = "2019",
month = dec,
doi = "https://doi.org/10.1109/CAMSAP45676.2019.9022522",
language = "الإنجليزيّة",
series = "2019 IEEE 8th International Workshop on Computational Advances in Multi-Sensor Adaptive Processing, CAMSAP 2019 - Proceedings",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "276--280",
booktitle = "2019 IEEE 8th International Workshop on Computational Advances in Multi-Sensor Adaptive Processing, CAMSAP 2019 - Proceedings",
address = "الولايات المتّحدة",
}