A self tuning fuzzy inference system for noise reduction


Duru N., Duru T.

ARTIFICIAL INTELLIGENCE AND SOFT COMPUTING - ICAISC 2004, cilt.3070, ss.290-295, 2004 (SCI İndekslerine Giren Dergi) identifier

  • Cilt numarası: 3070
  • Basım Tarihi: 2004
  • Dergi Adı: ARTIFICIAL INTELLIGENCE AND SOFT COMPUTING - ICAISC 2004
  • Sayfa Sayıları: ss.290-295

Özet

In this paper, a method for the reduction of noise in a speech signal is introduced. In the implementing of the method, firstly a high resolution frequency map of the signal is obtained. Each frequency band component of the signal is then segmented. Fuzzy inference system (FIS) is used for the determination of the noise contents of the segments. The output of the FIS is the suppression level of the segment. If the FIS decides that the segment contains only noise, then the segment is deleted or if the FIS decides that the segment is noise free, it is allowed to be passed without suppression. Since the signal to noise ratio (SNR) varies from case to case, the limits of the membership functions are tuned accordingly. This self tuning capability gives flexibility and robustness of the system.