Multi-scale fractal dimension for speaker identification system

Fulufhelo V. Nelwamondo, Unathi Mahola, Tshilidzi Marwala

Research output: Contribution to journalArticlepeer-review

8 Citations (Scopus)


This paper looks at the extraction of nonlinear turbulence information of the speech signal using Multi-Scale Fractal Dimension (MFD) as the additional feature to the convectional MFCC features. The MFD is estimated using both Box-Counting and Minkowiski-Bouligand dimensions. The proposed framework uses this feature extraction together with sub-band based speaker modeling rather than the wide-band approach. Results showed that the proposed framework with Box-Counting feature extraction improves the performance of the classical wideband approach with up 10% identification rate.

Original languageEnglish
Pages (from-to)1152-1157
Number of pages6
JournalWSEAS Transactions on Systems
Issue number5
Publication statusPublished - May 2006
Externally publishedYes


  • Box-counting
  • Minkowiski-Bouligand
  • Multi-scale fractal dimension
  • Speaker identification

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Computer Science Applications


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