Speaker identification using discrete wavelet packet transform technique with irregular decomposition

Jian Da Wu, Bing Fu Lin

Research output: Contribution to journalArticle

54 Citations (Scopus)

Abstract

This paper presents the study of speaker identification for security systems based on the energy of speaker utterances. The proposed system consisted of a combination of signal pre-process, feature extraction using wavelet packet transform (WPT) and speaker identification using artificial neural network. In the signal pre-process, the amplitude of utterances, for a same sentence, were normalized for preventing an error estimation caused by speakers' change in volume. In the feature extraction, three conventional methods were considered in the experiments and compared with the irregular decomposition method in the proposed system. In order to verify the effect of the proposed system for identification, a general regressive neural network (GRNN) was used and compared in the experimental investigation. The experimental results demonstrated the effectiveness of the proposed speaker identification system and were compared with the discrete wavelet transform (DWT), conventional WPT and WPT in Mel scale.

Original languageEnglish
Pages (from-to)3136-3143
Number of pages8
JournalExpert Systems with Applications
Volume36
Issue number2 PART 2
DOIs
Publication statusPublished - 2009 Mar

All Science Journal Classification (ASJC) codes

  • Engineering(all)
  • Computer Science Applications
  • Artificial Intelligence

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