papers AI Learner
The Github is limit! Click to go to the new site.

LOCATA challenge: speaker localization with a planar array

2019-01-25
Xinyuan Qian, Andrea Cavallaro, Alessio Brutti, Maurizio Omologo

Abstract

This document describes our submission to the 2018 LOCalization And TrAcking (LOCATA) challenge (Tasks 1, 3, 5). We estimate the 3D position of a speaker using the Global Coherence Field (GCF) computed from multiple microphone pairs of a DICIT planar array. One of the main challenges when using such an array with omnidirectional microphones is the front-back ambiguity, which is particularly evident in Task 5. We address this challenge by post-processing the peaks of the GCF and exploiting the attenuation introduced by the frame of the array. Moreover, the intermittent nature of speech and the changing orientation of the speaker make localization difficult. For Tasks 3 and 5, we also employ a Particle Filter (PF) that favors the spatio-temporal continuity of the localization results.

Abstract (translated by Google)
URL

http://arxiv.org/abs/1901.08983

PDF

http://arxiv.org/pdf/1901.08983


Comments

Content