LPC Vocoder Project

# LPC Vocoder Project - LPC Vocoder Project 1.0 Introduction...

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2/4/2004 11:18 AM 1 LPC Vocoder Project LPC Vocoder Project 1.0 Introduction The goal of this project is to build an LPC Vocoder based on the model of speech production shown below: The excitation or input, e(n) , is assumed to be either white noise or a quasi-periodic train of impulses (for voiced sounds). The linear system is assumed to be slowly time-varying, such that over short time intervals it can be described by the all-pole system function: 1 () 1 p k k k G Hz az = = The input and output signals are related by a difference equation of the form: 1 ( ) p k k xn axn k Gen = =− + Using standard methods of linear predictive (LP) analysis, we can find the set of prediction coefficients { α k } that minimize the mean-squared prediction error betweeh the signal x(n) and a predicted signal based on a linear combination of past samples; i.e., Linear, Time- Varying System LPC Parameters e(n), excitation x(n), speech output

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2/4/2004 11:18 AM 2 LPC Vocoder Project [] 22 1 (() ) ) p k k dn xn xn k α = <> = < > where < > represents averaging over a finite range of values of n . It can be shown that using one method of averaging, called the autocorrelation method , the optimum predictor coefficients { α k } satisfy a set of linear equations of the form: Ra=r where R is a p x p Toeplitz matrix made up of values of the autocorrelation sequence for x(n) , a is a p x 1 vector of prediction coefficients, and r is a p x 1 vector of autocorrelation values. In using LP techniques for speech analysis and synthesis, we make the assumption that the predictor coefficients { α k } are identical to the parameters {a k } of the speech model.
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## This note was uploaded on 12/29/2011 for the course ECE 259 taught by Professor Rabiner,l during the Fall '08 term at UCSB.

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LPC Vocoder Project - LPC Vocoder Project 1.0 Introduction...

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