@article{MAKHILLIJSSCEA20169528753,
    title = {Permutation Correction in Convolutive BSS Using MFCC Coefficients},
    journal = {International Journal of System Signal Control and Engineering Application},
    volume = {9},
    number = {5},
    pages = {157-165},
    year = {2016},
    issn = {1997-5422},
    doi = {ijssceapp.2016.157.165},
    url = {https://makhillpublications.co/view-article.php?issn=1997-5422&doi=ijssceapp.2016.157.165},
    author = {Mostafa,Hamid and},
    keywords = {BSS,permutation,MFCC coefficient,convolutive,frequency domain},
    abstract = {In this study, we propose a novel algorithm for solving the permutation ambiguity problem in
convolutive blind source separation of speech signals. Transferring convolutive mixtures into time-frequency
domain, enables us to separate source signals by employing instantaneous algorithms in each frequency bin.
After separation, the main challenge is the scale and permutation ambiguities which can imperil the separation
performance. Overcoming this challenge needs the reordering of all separated signals in each frequency bin
according to order of source signal. In this study we propose a new algorithm for reordering the separated
signals based on statistics of MFCC of speech signals. In each frequency bin, the separated subband signals
are transferred back to time-domain and their individual MFCC’s are extracted. Then, based on simple statistics
of the MFCC’s the permutation problem is resolved. The proposed algorithm drastically decreasesthe
computational complexity and as a result speeds up the permutation correction process.}
    }