This document summarizes digital modeling techniques for speech signals. It describes the vocal source and vocal tract that produce speech. It then discusses using sampling and techniques like PCM to digitally represent speech signals. Linear predictive coding is presented as a simple method to analyze speech that approximates samples as combinations of past signals. The summary concludes that linear prediction can be used for spectrum estimation by representing the vocal tract transfer function, pitch detection, and speech synthesis.

1. Digital modeling of SPEECH
SIGNAL

2. Speech Signal:
Vocal source: Lung, vocal cord and vocal gate
Vocal tract: start from voice gate till lip including throat and air tract.
In addition to that mouth cavity, nose cavity, lip.

4. Digital model

5.  Simply we can represent speech signal using the schemes
PCM,DPCM,DM etc..
 For example PCM technique,

Applying sampling theorem to the digital signal
of speech.(if the signal band width is W hertz then the sampling period
must be T<= 1/2W.)
 Measure of fidelity of PCM is SNR in this noise or error signal will be

7. Linear Predictive Method
 This is the simple method to analyze speech signal
 Basic idea sample of speech is approximated as linear combination of
past speech signals.

8.  Transfer function speech samples
 Let speech signal be x(n)
 With linear predictor
 Predictor error will be
 Predictor polynomial:

9. Use of Linear Prediction
 Spectrum estimation : If the predictor polynomial is assumed to represent
the denominator of the vocal tract transfer function, we can obtain
frequency response of vocal tract as
 Pitch detection
 Speech synthesis.
