• Create BookmarkCreate Bookmark
  • Create Note or TagCreate Note or Tag
  • PrintPrint
Share this Page URL
Help

Chapter 10. Speech Coding > Introduction to Speech Coding

10.1. Introduction to Speech Coding

In contrast to general audio coders for natural audio signals, speech coders are usually expected to handle human voice as an input signal. This means that a model-based signal analysis and synthesis can be used in a highly efficient manner. The most common and widely used model-based speech analysis system is linear predictive (LP) analysis, also known as linear predictive coding (LPC). In LPC analysis, a speech signal is decomposed into two components: a set of LP coefficients and a prediction error signal (residue). The LP coefficients allow the construction of an analysis filter, which removes short-term correlation in the speech signal and provides a prediction error signal. In this analysis, a speech signal is modeled as a convolution of the glottal vibration with the human vocal tract response. The analysis filter has approximately an inverse characteristic of the human vocal tract response, and the prediction error signal represents the human glottal vibration. LPC analysis also can be seen as a whitening operation of the speech spectrum in the frequency domain.

The simplest speech coder that uses LPC analysis is an LPC vocoder [Rabi78]. In such an LPC vocoder, LPC residual signals are modeled by a pulse train or noise, which are switched depending on a voiced/unvoiced (V/UV) decision. In this way, an LPC vocoder uses model-based parameters not only for the spectral envelope but also for the residual signals to represent speech signals; therefore, an LPC vocoder can encode speech signals at very low bit rates, such as 800 to 1200 bit/s. Figure 10.2 shows the structure of the LPC vocoder synthesizer.


PREVIEW

                                                                          

Not a subscriber?

Start A Free Trial


  
  • Creative Edge
  • Create BookmarkCreate Bookmark
  • Create Note or TagCreate Note or Tag
  • PrintPrint