Moreau N. Tools for Signal Compression. Applications to Speech and Audio Coding

Springer, 2011. — 205 p.In everyday life, we often come in contact with compressed signals: when using mobile telephones, MP3 players, digital cameras, or DVD players. The signals in each of these applications, telephone-band speech, high fidelity audio signal, and still or video images are not only sampled and quantized to put them into a form suitable for saving in mass storage devices or to send them across networks, but also compressed. The first operation is very basic and is presented in all courses and introductory books on signal processing. The second operation is more specific and is the subject of this book: here, the standard tools for signal compression are presented, followed by examples of how these tools are applied in compressing speech and musical audio signals. In the first part of this book, we focus on a problem which is theoretical in nature: minimizing the mean squared error. The second part is more concrete and qualifies the previous steps in seeking to minimize the bit rate while respecting the psychoacoustic constraints. We will see that signal compression consists of seeking not only to eliminate all redundant parts of the original signal but also to attempt the elimination of inaudible parts of the signal.
The compression techniques presented in this book are not new. They are explained in theoretical framework, information theory, and source coding, aiming to formalize the first (and the last) element in a digital communication channel: the encoding of an analog signal (with continuous times and continuous values) to a digital signal (at discrete times and discrete values). The techniques come from the work by C. Shannon, published at the beginning of the 1950s. However, except for the development of speech encodings in the 1970s to promote an entirely digitally switched telephone network, these techniques really came into use toward the end of the 1980s under the influence of working groups, for example, “Group Special Mobile (GSM)”, “Joint Photographic Experts Group (JPEG)”, and “Moving Picture Experts Group (MPEG)”.
The results of these techniques are quite impressive and have allowed the development of the applications referred to earlier. Let us consider the example of a music signal. We know that a music signal can be reconstructed with quasi-perfect quality (CD quality) if it was sampled at a frequency of 44.1 kHz and quantized at a resolution of 16 bits. When transferred across a network, the required bit rate for a mono channel is 705 kb/s. The most successful audio encoding, MPEG-4 AAC, ensures “transparency” at a bit rate of the order of 64 kb/s, giving a compression rate greater than 10, and the completely new encoding MPEG-4 HE-AACv2, standardized in 2004, provides a very acceptable quality (for video on mobile phones) at 24 kb/s for 2 stereo channels. The compression rate is better than 50!Part 1 Tools for Signal Compression
Scalar Quantization
Vector Quantization
Sub-band Transform Coding
Entropy Coding
Part 2 Audio Signal Applications
Introduction to Audio Signals
Speech Coding
Audio Coding
Audio Coding: Additional Information
Stereo Coding: A Synthetic Presentation
Part 3 MatLAB Programs
A Speech Coder
A Music Coder