IMPROVED SPEECH COMPRESSION USING LPC AND DWT APPROACH

Voice communication is a foremost communication application adapted to transferring the information in a verbal form. Owing to quite larger data size of voice signals in comparison to text, the need of speech compression techniques is greatly envisaged to reduce communicating data size. In this work, a hybrid model is presented that first reduces the signal noise and then compresses the voice signal. It works in three-stage? (i) spectral subtraction method to perform high level filtration, ii) Linear predictive coding (LPC) to reduce the signal noise and to reduce size, and finally iii) Discrete wavelet transforms (DWT) to perform the compression. High compression percentage with lesser distortion over the signal is observed in the results obtained. Evaluation on the basis of Mean Square Error (MSE), Peak Signal to Noise Ratio and Compression Percentage is done after the LPC and after the DWT.