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Speech enhancement using ICA with Bessel features
Ansvarig organisation
2011 (Engelska)Konferensbidrag, Publicerat paper (Refereegranskat) 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.

Ort, förlag, år, upplaga, sidor
Sarajevo: Univ of Sarajevo , 2011.
Nyckelord [en]
Bessel functions, Empirical Mode Decomposition, Independent component analysis, Speaker recognition, Speech enhancement
Nationell ämneskategori
Signalbehandling
Identifikatorer
URN: urn:nbn:se:bth-7373Lokalt ID: oai:bth.se:forskinfoC2E9CF8C7DE535D5C12579790036EAF7ISBN: 978-995899661-0 (tryckt)OAI: oai:DiVA.org:bth-7373DiVA, id: diva2:834981
Konferens
International Conference on Systems, Signals and Image Processing, IWSSIP
Tillgänglig från: 2012-09-18 Skapad: 2012-01-02 Senast uppdaterad: 2015-06-30Bibliografiskt granskad

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