Speaker identification using discrete wavelet packet transform technique with irregular decomposition

Jian Da Wu, Bing Fu Lin

研究成果: Article

54 引文 斯高帕斯(Scopus)

摘要

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.

原文English
頁(從 - 到)3136-3143
頁數8
期刊Expert Systems with Applications
36
發行號2 PART 2
DOIs
出版狀態Published - 2009 三月

    指紋

All Science Journal Classification (ASJC) codes

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

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