LECTURE 16: LINEAR PREDICTION-BASED REPRESENTATIONS

• Objectives:
  
  
  • Introduce analysis/synthesis systems
    
    
  • Discuss error analysis and gain-matching
    
    
  • Relate linear prediction coefficients to other spectral representations
    
    
  • Introduce reflection and prediction coefficent recursions
    
    
  • Lattice/ladder filter implementations

There is a classic textbook on this subject:

J.D. Markel and A.H. Gray, Linear Prediction of Speech, Springer-Verlag, New York, New York, USA, ISBN: 0-13-007444-6, 1976.

This lecture also includes material from two other textbooks:

J. Deller, et. al., Discrete-Time Processing of Speech Signals, MacMillan Publishing Co., ISBN: 0-7803-5386-2, 2000.

and,

L.R. Rabiner and B.W. Juang, Fundamentals of Speech Recognition, Prentice-Hall, Upper Saddle River, New Jersey, USA, ISBN: 0-13-015157-2, 1993.