DocumentCode :
2061559
Title :
Auxiliary function based iva using a source prior exploiting fourth order relationships
Author :
Yanfeng Liang ; Harris, J. ; Gaojie Chen ; Naqvi, Syed Mohsen ; Jutten, Christian ; Chambers, Jonathon
Author_Institution :
Sch. of Electron., Electr. & Syst. Eng., Loughborough Univ., Loughborough, UK
fYear :
2013
fDate :
9-13 Sept. 2013
Firstpage :
1
Lastpage :
5
Abstract :
Independent vector analysis (IVA) can theoretically avoid the permutation ambiguity present in frequency domain independent component analysis by using a multivariate source prior to retain the dependency between different frequency bins of each source. The auxiliary function based independent vector analysis (AuxIVA) is a stable and fast update IVA algorithm which includes no tuning parameters. In this paper, a particular multivariate generalized Gaussian distribution source prior is therefore adopted to derive the AuxIVA algorithm which can exploit fourth order relationships to better preserve the dependency between different frequency bins of speech signals. Experimental results confirm the improved separation performance achieved by using the proposed algorithm.
Keywords :
Gaussian distribution; blind source separation; independent component analysis; IVA; auxiliary function; fourth order relationships; frequency domain independent component analysis; independent vector analysis; multivariate generalized Gaussian distribution source prior; multivariate source prior; permutation ambiguity; speech signals; Algorithm design and analysis; Blind source separation; Equations; Frequency-domain analysis; Gaussian distribution; Speech; Vectors; AuxIVA; fourth order relationships; multivariate generalized Gaussian distribution;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Signal Processing Conference (EUSIPCO), 2013 Proceedings of the 21st European
Conference_Location :
Marrakech
Type :
conf
Filename :
6811750
Link To Document :
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