Frequency domain adaptive postfiltering for enhancement of noisy speech

Fang Ming Wang, Peter Kabal, Ravi P. Ramachandran, Douglas O'Shaughnessy

Research output: Contribution to journalArticlepeer-review

7 Scopus citations

Abstract

This paper presents a new frequency-domain approach to implement an adaptive postfilter for enhancement of noisy speech. The postfilter is described by a set of DFT coefficients which suppress noise in the spectral valleys and allow for more noise in formant regions which is masked by the speech signal. First, we perform an LPC analysis of the noisy speech and calculate the log magnitude spectrum of the input speech. After identifying the formants and valleys (by a new method), the log magnitude spectrum is modified to obtain the postfilter coefficients. The filtering operation is also done in the frequency domain through an FFT and an overlap-add strategy to get the postfiltered speech. Experimental results on 8-kHz-sampled speech show that this new frequency-domain approach results in enhanced speech of better perceptual quality than obtained by a time-domain method. This new method is especially efficient in eliminating high frequency noise and in preserving the weaker, high frequency formants in sonorant sounds.

Original languageEnglish (US)
Pages (from-to)41-56
Number of pages16
JournalSpeech Communication
Volume12
Issue number1
DOIs
StatePublished - Mar 1993

All Science Journal Classification (ASJC) codes

  • Software
  • Modeling and Simulation
  • Communication
  • Language and Linguistics
  • Linguistics and Language
  • Computer Vision and Pattern Recognition
  • Computer Science Applications

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