Audio Compression Using Perceptual and Huffman Coding

Digital Audio compression allows the efficient storage and transmission of audio data. The various audio compression techniques offer different levels of complexity, compressed audio quality and amount of data compression. It has become increasingly more important with the advent of fast and inexpensive microprocessors. Advances in digital audio technology are fueled by two sources: hardware

Developments and new signal processing techniques. When processors dissipated tens ofWattsof power and memory densities were on the order of kilobits per square inch, Portable playback devices like an MP3 player were not possible. Now, however, power Dissipation, memory densities, and processor speeds have improved by several orders of Magnitude. Advancements in signal processing are exemplified by Internet broadcast Applications: if the desired sound quality for an internet broadcast used 16-bit PCM Encoding at 44.1 kHz, such an application would require a 1.4 Mbps channel for a stereo Signal! Increasing hardware efficiency and an expanding array of digital audio Representation formats are giving rise to a wide variety of new digital audio applications. These applications include portable music playback devices, digital surround sound for Cinema, high-quality digital radio and television broadcast, Digital Versatile Disc (DVD), and many others. This paper concentrates on digital audio signal compression, a technique essential to the implementation of many digital audio applications. Digital audio signal compression is the removal of redundant or otherwise irrelevant information from a digital audio signal. A process that is useful for conserving both transmission bandwidth and storage space.

The standards of compression coding are very poorly described. It is defined of various methods of decoding but lacks details for encoding. This makes the implementation of a compression coder a greater task than might otherwise be expected. Normally, no information loss is acceptable when compressing digital audio such as programs, source code, and text documents. Entropy coding is the most commonly used method used for loss-less compression. It exploits the fact that all bit combinations are not likely to appear in the data, which is used in coding algorithms such as Huffman. This approach works for the data types mentioned above, however digital audio signals such as music and speech cannot be efficiently encoded with entropy coding. In this paper begin by defining some useful terminology.