UNSUPERVISED INCREMENTAL ADAPTATION USING MAXIMUM LIKELIHOOD SPECTRAL TRANSFORMATION

In a speech recognition system, a method of transforming speech feature vectors associated with speech data provided to the speech recognition system includes the steps of receiving likelihood of utterance information corresponding to a previous feature vector transformation, estimating one or more transformation parameters based, at least in part, on the likelihood of utterance information corresponding to a previous feature vector transformation, and transforming a current feature vector based on maximum likelihood criteria and/or the estimated transformation parameters, the transformation being performed in a linear spectral domain. The step of estimating the one or more transformation parameters includes the step of estimating convolutional noise Niα and additive noise Niβ for each ith component of a speech vector corresponding to the speech data provided to the speech recognition system.