and, therefore, mirror the slope of the actual signal. With each recurring sample and comparison, the step function can be increased or decreased as required. For example, if the signal is increasing rapidly, then the steps are increased one after the other in a form of step function by the encoding algorithm. Obviously, the reproduced signal is not a particu- larly exact representation of the input signal: In practice, it is pretty jagged. Filters, therefore, are used to smooth the transitions. CVSD is typically implemented at 32 Kbps, although it can be imple- mented at rates as low as 9,600 bps. At 16 to 24 Kbps, recognizability is still possible; down to 9,600, recognizability is seriously affected, although intelligibility is not. Linear Predictive Coding (LPC) We mention LPC here only because it has carved out a niche for itself in certain voice-related applications such as voice mail systems, automo- biles, aviation, and electronic games that speak to children. LPC is a Downloaded from Digital Engineering Library @ McGraw-Hill (www.digitalengineeringlibrary.com) Copyright © 2004 The McGraw-Hill Companies. All rights reserved. Any use is subject to the Terms of Use as given at the website. Telephony Telephony complex process, implemented completely in silicon, which allows for voice to be encoded at rates as low as 2,400 bps. The resulting quality is far from toll quality, but it is certainly intelligible and its low bit-rate capability gives it a distinct advantage over other systems. LPC relies on the fact that each sound created by the human voice has unique attributes, such as frequency range, resonance, and loudness, among others. When voice samples are created in LPC, these attributes are used to generate "prediction coefficients." These predictive coeffi- cients represent linear combinations of previous samples, hence the name-Linear Predictive Coding. Prediction coefficients are created by taking advantage of the known formants of speech, which are the resonant characteristics of the mouth and throa