This project is a hardware-based voice compression method. The objective of this project is to construct and demonstrate the various ways original sound or voice can be compressed to reduce size using Matlab and hardware tools. Multimedia files in general need plenty of disk space for storage apart from being unwieldy for communication purposes and sound files are no exception, hence compression of these files has become a necessity and is a ripe subject for research. There are many ways to compress sound files and this thesis seeks to explain two major types. The field of signal processing has enjoyed several analysis tools in the past. One of the more recent developments in this field has been the emergence of a new transform, the wavelet transform. In fact, its use is not restricted to signal processing alone, but ranges over such diverse fields as image processing, communications, mathematics, computer science to name a few. Wavelet transforms, in their different guises, have come to be accepted as a set of tools useful for various applications. Linear predictive coding (LPC) is a tool used mostly in audio signal processing and speech processing for representing the spectral envelope of a digital signal of speech in compressed form, using the information of a linear predictive model. It is one of the most powerful speech analysis techniques, and one of the most useful methods for encoding good quality speech at a low bit rate and provides extremely accurate estimates of speech parameters. All these compression procedures are further discussed in the thesis. THE WAVELET TRANSFORM, LINEAR PREDICTIVE CODING, HARDWARE, MATLAB
