Performance of nonlinear speech enhancement using phase space reconstruction

Michael T. Johnson, Andrew C. Lindgren, Richard J. Povinelli, Xiaolong Yuan

Research output: Contribution to journalConference articlepeer-review

15 Scopus citations


This paper presents the implementation of two nonlinear noise reduction methods applied to speech enhancement. The methods are based on embedding the noisy signal in a high-dimensional reconstructed phase space and applying singular value decomposition to project the signal into a lower dimension. The advantages of these nonlinear methods include that they do not require explicit models of noise spectra and do not have the typical "musical tone" side effects associated with traditional linear speech enhancement methods. The proposed nonlinear methods are compared with traditional speech enhancement techniques, including spectral subtraction, Wiener filtering, and Ephraim-Malah filtering, on example speech utterances with additive white noise for a variety of SNR levels. The results show that the local nonlinear noise reduction method outperforms Wiener filtering and spectral subtraction but not Ephraim-Malah filtering, as had been suggested by previous studies.

Original languageEnglish
Pages (from-to)920-923
Number of pages4
JournalICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
StatePublished - 2003
Event2003 IEEE International Conference on Accoustics, Speech, and Signal Processing - Hong Kong, Hong Kong
Duration: Apr 6 2003Apr 10 2003

ASJC Scopus subject areas

  • Software
  • Signal Processing
  • Electrical and Electronic Engineering


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