Description of algorithms for Ben-Gurion University Submission to the LOCATA challenge
This is an incremental contribution to audio signal processing for robotics and microphone arrays, addressing specific tasks in a benchmark challenge.
The paper tackled source localization for the LOCATA challenge using direction of arrival estimation with direct-path dominance tests and k-means clustering, achieving results for stationary sources with Nao and Eigenmike arrays.
This paper summarizes the methods used to localize the sources recorded for the LOCalization And TrAcking (LOCATA) challenge. The tasks of stationary sources and arrays were considered, i.e., tasks 1 and 2 of the challenge, which were recorded with the Nao robot array, and the Eigenmike array. For both arrays, direction of arrival (DOA) estimation has been performed with measurements in the short time Fourier transform domain, and with direct-path dominance (DPD) based tests, which aim to identify time-frequency (TF) bins dominated by the direct sound. For the recordings with Nao, a DPD test which is applied directly to the microphone signals was used. For the Eigenmike recordings, a DPD based test designed for plane-wave density measurements in the spherical harmonics domain was used. After acquiring DOA estimates with TF bins that passed the DPD tests, a stage of k-means clustering is performed, to assign a final DOA estimate for each speaker.