Application of a weighted projection measure for robust hidden Markov model based speech recognition

The use of a projection-based cepstral measure for speech recognition in noise is investigated. Interpretations of the measure´s spectral and perceptual significance are given, along with its application to cepstral, melcepstral, and delta parameters. It is shown how the projection measure can be incorporated into a continuous density hidden Markov model system in the form of a weighted measure. Both the case where these densities are unimodal Gaussians and mixtures of Gaussians are addressed. In recognition experiments, the weighted projection measure significantly outperformed the standard weighted Euclidean or Gaussian distance measure