Abstract
This paper compares the performance of several blind source separation (BSS) algorithms in environments of varying reverberation, noise, microphone spacing, and sparsity. of particular interest are two frequency domain algorithms: one Cascaded ICA with Intervention Alignment (CICAIA), and one algorithm by Pham, Servire, and Boumaraf. the former is found to work exceptionally well in high noise, low microphone spacing environments. the latter proves to work exceptionally well in high SNR and moderate- to widely spaced arrays. in addition, while the literature on BSS algorithms is extensive, their performance under varying noise conditions has not been widely explored. Also, though usually BSS results for given reverberation times are provided, the sparseness of the room responses (with the same reverberation times) are not. Here we empirically demonstrate that the sparseness of the source-to-sensor impulse responses dramatically effects BSS performance and therefore should always be reported. © 2011 IEEE.
Recommended Citation
C. Osterwise and S. Grant, "A Comparison of BSS Algorithms in Harsh Environments," 2011 IEEE International Conference on Signal Processing, Communications and Computing, ICSPCC 2011, article no. 6061823, Institute of Electrical and Electronics Engineers, Nov 2011.
The definitive version is available at https://doi.org/10.1109/ICSPCC.2011.6061823
Department(s)
Electrical and Computer Engineering
Keywords and Phrases
blind source separation (BSS); convolutive mixture; frequency-domain ICA; permutation problem
International Standard Book Number (ISBN)
978-145770894-7
Document Type
Article - Conference proceedings
Document Version
Citation
File Type
text
Language(s)
English
Rights
© 2024 Institute of Electrical and Electronics Engineers, All rights reserved.
Publication Date
17 Nov 2011
