In this section
@inproceedings{Hafezi:2017:10.23919/EUSIPCO.2017.8081406,
author = {Hafezi, S and Moore, AH and Naylor, PA},
doi = {10.23919/EUSIPCO.2017.8081406},
pages = {1240--1244},
title = {Multiple DOA estimation based on estimation consistency and spherical harmonic multiple signal classification},
url = {http://dx.doi.org/10.23919/EUSIPCO.2017.8081406},
year = {2017}
}
TY - CPAPER
AB - © EURASIP 2017. A common approach to multiple Direction-of- Arrival (DOA) estimation of speech sources is to identify Time- Frequency (TF) bins with dominant Single Source (SS) and apply DOA estimation such as Multiple Signal Classification (MUSIC) only on those TF bins. In the state-of-the-art Direct Path Dominance (DPD)-MUSIC, the covariance matrix, used as the input to MUSIC, is calculated using only the TF bins over a local TF region where only a SS is dominant. In this work, we propose an alternative approach to MUSIC in which all the SS-dominant TF bins for each speaker across TF domain are globally used to improve the quality of covariance matrix for MUSIC. Our recently proposed Multi-Source Estimation Consistency (MSEC) technique, which exploits the consistency of initial DOA estimates within a time frame based on adaptive clustering, is used to estimate the SS-dominant TF bins for each speaker. The simulation using spherical microphone array shows that our proposed MSEC-MUSIC significantly outperforms the state-of-the-art DPD-MUSIC with less than 6:5° mean estimation error and strong robustness to widely varying source separation for up to 5 sources in the presence of realistic reverberation and sensor noise.
AU - Hafezi,S
AU - Moore,AH
AU - Naylor,PA
DO - 10.23919/EUSIPCO.2017.8081406
EP - 1244
PY - 2017///
SP - 1240
TI - Multiple DOA estimation based on estimation consistency and spherical harmonic multiple signal classification
UR - http://dx.doi.org/10.23919/EUSIPCO.2017.8081406
ER -
Speech and Audio Processing Lab
CSP Group, EEE Department
Imperial College London
Exhibition Road, London, SW7 2AZ, United Kingdom