A Noise Cancellation Method Based on Wavelet Transform

In this paper, we present a frequency band threshold based on wavelet transform (FBT) noise cancellation method. The noise cancellation is enable to improve on the articulation of the speech. Although the edge information of the speech is very important for recognition system to use, most traditional noise cancellation methods based on spectrum analysis smooth these edges of the original speech. We hope to get a noise cancellation method that keeps these edges information. We knew that the performance of edge detection based on wavelet transform is very high. So we use wavelet transform for noise cancellation. Noise cancellation methods based on wavelet transform were referred to papers [1][2]. The method was given by paper [1] is not real-time. Hence this method is difficult to be used a practical system. Although the real-time property of the noise cancellation method was referred to paper [2] is perfect, the aural performance is defective. This method has a single threshold (ST). It ignored the difference of the frequency bands. FBT is presented by us in this paper possesses two characteristics as follow: (1) These thresholds depend on frequency bands. (2) These thresholds are self-adjusting. Based on two judgement standards---signal noise rate (impersonal standard) and the articulation of the speech (subjective standard), we did comparison experiments between FBT and ST. Although FBT’s signal noise rate inferior to the ST’s, FBT’s waveform distortion is less than ST’s and FBT’s articulation of the speech is remarkable superior to the ST’s. We particularly analyzed the causes of the phenomena and did the comparison experiments of these two methods on the same speech recognition system. The conclusion is FBT is superior to ST.