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Speech enhancement using ICA with Bessel features
Responsible organisation
2011 (English)Conference paper (Refereed) Published
Abstract [en]

The Independent Component Analysis with Reference (ICA R) also called as constrained ICA (cICA) extracts only the desired source signals from the mixture of source signals by incorporating some prior information into the separation process. To overcome the problem of designing the reference signal when there is no prior information about the desired signal in the cICA, an improved method is proposed to use a different speech signal generated by the same physical source. The cICA is extended to use Bessel coefficients of the observed signals and the reference signal for processing as they converge faster than the other transformations. Since the Bessel functions provide the desired properties, efficient in representing speech signals, less memory storage they have been exploited in speech processing [1]. The results demonstrate the efficiency of the proposed method.

Place, publisher, year, edition, pages
Sarajevo: Univ of Sarajevo , 2011.
Keyword [en]
Bessel functions, Empirical Mode Decomposition, Independent component analysis, Speaker recognition, Speech enhancement
National Category
Signal Processing
Identifiers
URN: urn:nbn:se:bth-7373Local ID: oai:bth.se:forskinfoC2E9CF8C7DE535D5C12579790036EAF7ISBN: 978-995899661-0 OAI: oai:DiVA.org:bth-7373DiVA: diva2:834981
Conference
International Conference on Systems, Signals and Image Processing, IWSSIP
Available from: 2012-09-18 Created: 2012-01-02 Last updated: 2015-06-30Bibliographically approved

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CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
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