In this section
@article{Evers:2020:10.1109/TASLP.2020.2990485,
author = {Evers, C and Lollmann, HW and Mellmann, H and Schmidt, A and Barfuss, H and Naylor, PA and Kellermann, W},
doi = {10.1109/TASLP.2020.2990485},
journal = {IEEE/ACM Transactions on Audio, Speech and Language Processing},
pages = {1620--1643},
title = {The LOCATA challenge: acoustic source localization and tracking},
url = {http://dx.doi.org/10.1109/TASLP.2020.2990485},
volume = {28},
year = {2020}
}
TY - JOUR
AB - The ability to localize and track acoustic events is a fundamental prerequisite for equipping machines with the ability to be aware of and engage with humans in their surrounding environment. However, in realistic scenarios, audio signals are adversely affected by reverberation, noise, interference, and periods of speech inactivity. In dynamic scenarios, where the sources and microphone platforms may be moving, the signals are additionally affected by variations in the source-sensor geometries. In practice, approaches to sound source localization and tracking are often impeded by missing estimates of active sources, estimation errors, as well as false estimates. The aim of the LOCAlization and TrAcking (LOCATA) Challenge is an openaccess framework for the objective evaluation and benchmarking of broad classes of algorithms for sound source localization and tracking. This paper provides a review of relevant localization and tracking algorithms and, within the context of the existing literature, a detailed evaluation and dissemination of the LOCATA submissions. The evaluation highlights achievements in the field, open challenges, and identifies potential future directions.Index Terms—Acoustic signal processing, Source localization, Source tracking, Reverberation.
AU - Evers,C
AU - Lollmann,HW
AU - Mellmann,H
AU - Schmidt,A
AU - Barfuss,H
AU - Naylor,PA
AU - Kellermann,W
DO - 10.1109/TASLP.2020.2990485
EP - 1643
PY - 2020///
SN - 2329-9290
SP - 1620
TI - The LOCATA challenge: acoustic source localization and tracking
T2 - IEEE/ACM Transactions on Audio, Speech and Language Processing
UR - http://dx.doi.org/10.1109/TASLP.2020.2990485
UR - https://ieeexplore.ieee.org/document/9079214
UR - http://hdl.handle.net/10044/1/78133
VL - 28
ER -
Speech and Audio Processing Lab
CSP Group, EEE Department
Imperial College London
Exhibition Road, London, SW7 2AZ, United Kingdom