LECTURE 25: CONTINUOUS MIXTURE DENSITIES

• Objectives:
  
  
  • Review the EM algorithm
    
    
  • Introduce continuous mixture densities
    
    
  • Understand why they are useful in speech recognition
    
    
  • Develop reestimation equations for the parameters of a mixture density

This lecture combines material from the course textbook:

X. Huang, A. Acero, and H.W. Hon, Spoken Language Processing - A Guide to Theory, Algorithm, and System Development, Prentice Hall, Upper Saddle River, New Jersey, USA, ISBN: 0-13-022616-5, 2001.

and information found in most standard speech textbooks:

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