Application Of The Wavelet Transformation In The Denoising Of Uyghur Specch Signal

In practical application， such as speech telecommunication， speech synthesis，speaker recognition， the degradation of Uyghur speech by all kinds of noise is inevitableand it affects the performance of the speech equipments very badly. So，it is necessary todenoise for the degraded speech. De-noising of speech signal has become an importantbranch of digital signal processing，its main function is reducing noise of noised Uyghurspeech signal，and enhancing voice definition.There is various de-noising algorithm of speech now， among them， wavelet hasgood localizing quality at time domain and frequency domain simultaneously and thecharacteristic of multi-resolution ratio analysis， it implements multiscale analysis to thesignal by the translation and dilation of the mother wavelet， it can effectively extractinformation from signal. So it can fulfill all kinds of wave-filtering needs such as low-pass，high-pass， sink wave， random noise denoising. Compare with traditional wave-filteringmethods， wavelet has incomparable advantage. Wavelet has become an effective means ofsignal analysis.Wavelet de-noising has three main method: modulus maxima de-noising method，correlation de-noising method and thresholding de-noising method. Among them waveletthresholding de-noising gets extensive application because of its simplecalculation.Donoho’s hard thresholding and soft thresholding algorithm is frequently usedto de-noising and has obtained a good effect now. Discontinuity of hard thresholdingfunction results signal after de-noising has obviously noise. Soft thresholding function hasgood continuilty but it has aconstant deviation of the estimated value wavelet coefficientfrom the noised signal wavelet coefficient. It will be too smooth when the noise is veryirregular.This thesis presented a newthresholding function whitch based on solve the shortageof soft and hard thresholding function. newthresholding function not only overcomes thediscontinuity of hard thresholding function but also solves the constant deviation of softthresholding function. experiment simulation demonstrated that the improved thresholdingfunction can remove the white noise in which the Uyghur speech signal contain soeffectively. And its signal-to-noise ratio is superior to the traditional thresholding function.It can obtain better de-noising effect. So the thresholding function in this thesis has a lot ofsuperiority and efficiency.