A COMPARISON OF CONSTRAINED TRAJECTORY SEGMENT MODELS FOR LARGE VOCABULARY SPEECH RECOGNITION

This paper compares parametric and nonparametric constrained-mean traj ectory segment models for large vocabulary speech recognition, extendi ng distribution clustering techniques to handle polynomial mean trajec tory 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.