Voice Coders

  • Priyabrata Sinha


In Chap. 7, we saw various techniques for representing the waveform of speech signals in such a way that the number of bits used to represent each sample was minimized. Generally, such algorithms exploit the inherent redundancy and spectral characteristics of the speech signal, but nevertheless the original waveform can be reproduced at the decoder to a large extent. However, these Waveform Coder algorithms did not provide a very high compression ratio; hence they are not very effective when low output data rates are required in an application, either due to constraints in the memory available for storing the encoded speech or due to limited communication bandwidth. In this chapter, we will shift our focus to speech encoding algorithms that attempt to parameterize each segment of speech by encoding the characteristics of a human speech production model rather than the waveform itself. This class of speech coders, known as Voice Coders or simply Vocoders, provides applications with a greater degree of speech compression, albeit at the cost of not being able to reproduce the speech waveform itself. There are a large variety of Vocoder standards providing various capabilities, including several standards for mobile communications such as TIA IS54 VSELP and ETSI GSM Enhanced Full Rate ACELP. Only a few representative coding techniques suitable for embedded applications are described in this chapter, including some specific standardized vocoders (G.728, G.729, and G.723.1) and an open-source speech coding algorithm (Speex).


Vector Quantization Vocal Tract High Compression Ratio Pitch Period Speech Frame 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer Science+Business Media, LLC 2010

Authors and Affiliations

  1. 1.Microchip Technology, Inc.ChandlerUSA

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