A Region-Growing Permutation Alignment Approach in Frequency-Domain Blind Source Separation of Speech Mixtures

Download
  1. (PDF, 650 KB)
  2. Get@NRC: A Region-Growing Permutation Alignment Approach in Frequency-Domain Blind Source Separation of Speech Mixtures (Opens in a new window)
DOIResolve DOI: http://doi.org/10.1109/TASL.2010.2052244
AuthorSearch for: ; Search for: ; Search for:
TypeArticle
Journal titleIEEE Transaction on Audio, Speech and Language Processing
Volume19
Issue3
Pages549557; # of pages: 9
SubjectTerms—Blind source separation (BSS); convolutive mixture; frequency domain; permutation problem; power ratio; region growing
AbstractThe convolutive blind source separation (BSS) problem can be solved efficiently in the frequency domain, where instantaneous BSS is performed separately in each frequency bin. However, the permutation ambiguity in each frequency bin should be resolved so that the separated frequency components from the same source are grouped together. To solve the permutation problem, this paper presents a new alignment method based on an inter-frequency dependence measure: the powers of separated signals. Bin-wise permutation alignment is applied first across all frequency bins, using the correlation of separated signal powers; then the full frequency band is partitioned into small regions based on the bin-wise permutation alignment result. Finally, region-wise permutation alignment is performed in a region-growing manner. The region-wise permutation correction scheme minimizes the spreading of the misalignment at isolated frequency bins to others, hence to improve permutation alignment. Experiment results in simulated and real environments verify the effectiveness of the proposed method. Analysis demonstrates that the proposed frequency-domain BSS method is computationally efficient.
Publication date
LanguageEnglish
AffiliationNational Research Council Canada; NRC Institute for Microstructural Sciences
Peer reviewedYes
NPARC number17355694
Export citationExport as RIS
Report a correctionReport a correction
Record identifier5100f342-81b4-4a3e-996c-94d88621c090
Record created2011-03-26
Record modified2016-05-09
Bookmark and share
  • Share this page with Facebook (Opens in a new window)
  • Share this page with Twitter (Opens in a new window)
  • Share this page with Google+ (Opens in a new window)
  • Share this page with Delicious (Opens in a new window)