On the efficient speech feature extraction based on independent component analysis

Jong Hwan Lee, Te Won Lee, Ho Young Jung, Soo Young Lee

Research output: Contribution to journalArticlepeer-review

10 Citations (Scopus)


A new efficient code for speech signals is proposed. To represent speech signals with minimum redundancy we use independent component analysis to adapt features (basis vectors) that efficiently encode the speech signals. The learned basis vectors are sparsely distributed and localized in both time and frequency. Time-frequency analysis of basis vectors shows the property similar with the critical bandwidth of human auditory system. Our results suggest that the obtained codes of speech signals are sparse and biologically plausible.

Original languageEnglish
Article number402005
Pages (from-to)235-245
Number of pages11
JournalNeural Processing Letters
Issue number3
Publication statusPublished - 2002
Externally publishedYes


  • Auditory system
  • Critical band
  • Feature extraction
  • Independent component analysis
  • Sparse code
  • Speech signal processing

ASJC Scopus subject areas

  • Software
  • Neuroscience(all)
  • Computer Networks and Communications
  • Artificial Intelligence


Dive into the research topics of 'On the efficient speech feature extraction based on independent component analysis'. Together they form a unique fingerprint.

Cite this