Title :
Frequency Domain Passive Broadband Speaker Localization using a Permutation-Free Blind Source Separation Algorithm
Author_Institution :
SoftMax, San Diego, CA, USA
Abstract :
Traditional passive broadband source localization techniques like maximum likelihood estimation and MUSIC have shown difficulties in situations where multiple correlating source signals are interfering with each other. Blind source separation (BSS) algorithms on the other hand have demonstrated good performance in separating correlated mixture signals into independent sources. In this paper it will be shown that the performance of traditional source localization algorithms can be improved by using a permutation-free frequency domain BSS algorithm as a front end. In addition a source localization method based solely on information gained from the separated BSS solution and sensor array architecture is presented. The methodologies are illustrated in an undercomplete acoustic scenario involving 3 speech sources and a 6 element microphone array.
Keywords :
blind source separation; frequency-domain analysis; maximum likelihood estimation; speech processing; MUSIC; correlated mixture signal separation; element microphone array; frequency domain passive broadband speaker localization; maximum likelihood estimation; permutation-free blind source separation algorithm; source localization algorithms; source signal correlation; speech sources; Acoustic arrays; Acoustic sensors; Blind source separation; Frequency domain analysis; Maximum likelihood estimation; Microphone arrays; Multiple signal classification; Sensor arrays; Source separation; Speech; Passive source localization; source separation;
Conference_Titel :
Acoustics, Speech and Signal Processing, 2007. ICASSP 2007. IEEE International Conference on
Conference_Location :
Honolulu, HI
Print_ISBN :
1-4244-0727-3
DOI :
10.1109/ICASSP.2007.366325