Background noises interfere with communication devices such as mobile telephone, digital hearing aid, etc. Therefore noise reduction (NR) part for limiting the effect of these noises is important. The paper proposes a noise reduction method based on the soft decision-making by the fuzzy inference system (FIS). The different characteristics of noises frequently occurring are used for creating the fuzzy decision rule base of the FIS. The FIS have two input parameters: the average energy and the difference of the average energy. The analysis of the FIS is done in the domain of the perceptual wavelet packet transform (PWPT) that is the human’s psychoacoustic model. The output of the FIS is used to modify the PWPT coefficients in such a way that it is more likely that the noise components are reduced while the speech signal is enhanced. The enhanced speech signal is the result of the inverse perceptual wavelet packet transform (IPWPT) of the modified coefficients. The experiment results show that the proposed method gives lower distortion than do the conventional methods especially when the input signal-to-noise ratio (SNR) is low; e.g. at SRN at 0dB the proposed method improves the output SNR level up to 4.18dB.
Defect Recognition in Concrete Ultrasonic Detection Based on Wavelet Packet Transform and Stochastic Configuration Networks
