Title :
A comparison of constrained trajectory segment models for large vocabulary speech recognition
Author :
Kannan, Ashvin ; Ostendorf, Mari
Author_Institution :
Nuance Commun., Menlo Park, CA, USA
fDate :
5/1/1998 12:00:00 AM
Abstract :
This paper compares parametric and nonparametric constrained-mean trajectory segment models for large vocabulary speech recognition, extending distribution clustering techniques to handle polynomial mean trajectory models for robust parameter estimation. The parametric model has fewer free parameters and gives similar recognition performance to the nonparametric model, but has higher recognition costs
Keywords :
parameter estimation; pattern recognition; speech recognition; constrained trajectory segment models; distribution clustering techniques; large vocabulary speech recognition; nonparametric constrained-mean trajectory; parametric constrained-mean trajectory; polynomial mean trajectory models; recognition costs; recognition performance; robust parameter estimation; Context modeling; Gaussian distribution; Gaussian processes; Hidden Markov models; Parametric statistics; Polynomials; Speech recognition; Stochastic processes; Trajectory; Vocabulary;
Journal_Title :
Speech and Audio Processing, IEEE Transactions on
