Title :
Indoor sound source localization and number estimation using infinite Gaussian mixture models
Author :
Longji Sun ; Qi Cheng
Author_Institution :
Sch. of Electr. & Comput. Eng., Oklahoma State Univ., Stillwater, OK, USA
Abstract :
This paper deals with sound source number estimation and localization in indoor environments using a circular microphone array. The problem is approached in the time-frequency (TF) domain by performing a single source localization algorithm at selected TF points and consequently generating one direction of arrival (DOA) estimate at each of the points. The resulted DOA estimates are assumed from an infinite Gaussian mixture model. The number and the means of Gaussian components correspond to the number and the true DOAs of the sources, respectively. The proposed algorithm is tested using real experiments.
Keywords :
Gaussian processes; acoustic signal processing; direction-of-arrival estimation; microphone arrays; mixture models; time-frequency analysis; DOA estimation; TF domain; circular microphone array; direction of arrival estimation; indoor sound source localization estimation; indoor sound source number estimation; infinite Gaussian mixture model; time-frequency domain; Arrays; Direction-of-arrival estimation; Estimation; Gaussian mixture model; Microphones; Speech; Multiple sound source localization; infinite Gaussian mixture model; source number estimation;
Conference_Titel :
Signals, Systems and Computers, 2014 48th Asilomar Conference on
Print_ISBN :
978-1-4799-8295-0
DOI :
10.1109/ACSSC.2014.7094646
