• DocumentCode
    2190335
  • Title

    Text-independent MFCCs vectors classification improvement using local ICA

  • Author

    Rouigueb, A. ; Chitroub, Salim ; Bouridane, Ahmed

  • Author_Institution
    Ecole Militaire Polytech., Algiers, Algeria
  • fYear
    2013
  • fDate
    22-25 Sept. 2013
  • Firstpage
    1
  • Lastpage
    6
  • Abstract
    In this paper, we propose a new classification scheme of MFCCs vectors in the context of speaker identification. The solution is built around the binary SVM classification between each speaker class and the background model class over the underlying spaces of the local independent components analysis using clustering. Experiments have been conducted on a sample of the MOBIO corpus.
  • Keywords
    independent component analysis; speaker recognition; support vector machines; vectors; MOBIO corpus; binary SVM classification; classification scheme; clustering; independent component analysis; local ICA; speaker identification; text-independent MFCC vector; Adaptation models; Clustering algorithms; Speaker recognition; Speech; Support vector machines; Training; Vectors; Speaker recognition; background model; local independent component analysis; text-independent;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Machine Learning for Signal Processing (MLSP), 2013 IEEE International Workshop on
  • Conference_Location
    Southampton
  • ISSN
    1551-2541
  • Type

    conf

  • DOI
    10.1109/MLSP.2013.6661941
  • Filename
    6661941
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=2190335