Threshold

Abstract: Speech signal analysis is one of the important areas of research in multimedia applications. In paper the speech enhancement is performed using DWT with thresholding and types of wavelet are used to denoised the audio signals and enhance speech and audio signal quality. Our main objective is to reduce noise from system which is heavily dependent on the specific context and application. As, we want to increase the intelligibility or improve the overall speech perception quality. After studying and analyzing, we have concluded that Noise reduction technology is aimed at reducing unwanted ambient sound, and is implemented throughout two different methods with parameters such as SNR, PSNR, MSE and the Time to reduce the noise for noisy signals for removing noise. We can analyze the denoised signal by signal to noise ratio (SNR), mean square error (MSE), Threshold values and elapsed time analysis. In the DWT Coif wavelet with soft threshold is best as compared to coif hard threshold, in DWT soft threshold results are has been best as compared to hard threshold