Speaker identification using multilayer perceptrons and radial basis function networks

Man Wai Mak, W. G. Allen, G. G. Sexton

Research output: Journal article publicationJournal articleAcademic researchpeer-review

27 Citations (Scopus)


This paper compares the Multilayer Perceptrons network (trained by the backpropagation algorithm) and the Radial Basis Function networks in the task of speaker identification. The experiments were carried out on 200 utterances (10 digits) of 10 speakers. LPC-derived cepstrum coefficients were used as the speaker specific features. The results showed that the Multilayer Perceptrons networks were superior in memory usage and classification time. However, they suffered from long training time and the error rate was slightly higher than that of Radial Basis Function networks.
Original languageEnglish
Pages (from-to)99-117
Number of pages19
Issue number1
Publication statusPublished - 1 Jan 1994
Externally publishedYes


  • backpropagation
  • Multilayer Perceptrons
  • Neural networks
  • pattern recognition
  • Radial Basis Function
  • speaker recognition
  • speech processing

ASJC Scopus subject areas

  • Computer Science Applications
  • Cognitive Neuroscience
  • Artificial Intelligence


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