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ECE 259 Digital Speech Processing LPC vocoder project

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Title: ECE 259 Digital Speech Processing LPC vocoder project


1
ECE 259Digital Speech ProcessingLPC vocoder
project
  • Teacher Prof Lawrence Rabiner
  • Student Vinay Melkote

2
LPC analysis
  • Predict speech sample s(n) from p previous
    samples with error minimisation.
  • s(n) S ai s(n-i) e(n) i1,2,,p
  • Exploits correlation in speech

3
Philosophy
  • Vocal tract can be modelled as loseless tubes
  • The transfer function has poles and zeros
  • H(z) N(z)/D(z)
  • The coefficients of the denominator D(z)
    polynomial are ai s and determine the resonances
    or formants

4
Finding ai s
  • Since the ai characterise formants, they vary
    with time as the utterances change
  • Assumed constant over a frame of speech
  • To find ai minimise error over that frame
  • Windowed speech - autocorrelation method
  • Windowed error covariance method

5
Lattice implementation
  • On the fly method
  • Find reflection coefficients
  • Use Durbins recursion to find ai

6
LPC synthesis
  • Based on the following model of speech production

Figure from Digital Processing of Speech Signals
, by Lawrence Rabiner and Ronald Schafer
7
LPC Vocoder
  • Analyse get ai s and gains
  • Synthesize reconstruct error signal, extract
    window and filter through vocal tract filter,
    overlap add

8
The Matlab code
waveanalx
vinlpcx
frameconst
Pitch contour
u(n)
Gain compute
Error sum
synthesizex
Reconstructed speech
9
Synthesized speech samples
  • Original
  • N240, L80,p 12
  • N generated
  • L generated
  • Hamming window

10
Gain quantized
  • Original
  • No of bits
  • 16
  • 12
  • 8
  • 4
  • 2
  • 1

11
Log area parameter quantized
  • Alpha quantized
  • Log area parameter quantized
  • No of bits
  • 12
  • 8
  • 6
  • 4
  • 2

12
Log area and gain quantized
  • No of bits No of bits
  • for log area for gain
  • 8 8
  • 8 4
  • 8 2
  • 6 8
  • 6 4
  • 6 2
  • 4 8
  • 4 4
  • 4 2

13
Conclusion
  • LPC synthesis gives speech which is highly
    intelligible and of good quality
  • Quantizing the required gain and vocal tract
    parameters can still maintain intelligibility and
    appreciable quality
  • Thus LPC helps to achieve low bit rate coding of
    speech
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