ee classes above but are a mixture. Speech occupies a total bandwidth of approximately 7 kHz, but the spectrum has a typical average value of 3 kHz (combined voiced and unvoiced sounds and dependent on age and gender). As far as hearing is concerned, the auditory canal acts as a resonant cavity at this 3-kHz average frequency. Figure 1.2 shows the spectrum of a sample speech segment. As can be seen from the spectra in the figure, there is little energy above 3.5 kHz. Overall, speech-encoding algorithms can be made less complex than general encoding by concentrating (through filters) on this region. Additionally, because traditional voice tele- communications allow a passband of less than 4 kHz, fricative-dependent high frequencies are removed. This can cause occasional issues with fricative names, such as "Frank." Speech-Coding Principles Fig. 1.2 Spectrum of a sample speech segment. Frequency (kHz) The subject area of speech production has a vast literature, and this introduction has served to consider only the basic issues. Classification of Speech Coders In most telecommunications applications, the original speech signal is compressed for improved storage density and more effective use of the transmission system. On this basis, the encoding process can be designated lossy or lossless. In the latter case, the original wave- form is reproduced exactly in end-to-end network propagation. In fact, lossless coding is most suitable for source material, which generally fits a certain statistical behavior. In the case of a speech signal, this means a source in which low-frequency content dominates. Examples of lossless coding include Variable Length Coding (VLC) schemes, such as Huffman and arithmetic coding. Although lossy systems can imply sacrifices in perceived quality, they are widely accepted. Quantization, for example, in which the speech samples are allocated prescribed values, is the simplest and most fundamental lossy technique used by all digital speech-coding schemes. Speech coding techniques can be classif