Patent ID: 9251784
Filing Date: 2016-02-02
CPC Classification: G10L

Claim Text:
1. A method for training a transformation matrix of a feature vector for an acoustic model, comprising: (a) extracting the feature vector from a speech signal; (b) training the transformation matrix of the feature vector, the transformation matrix maximizing an objective function having a regularization term; and (c) transforming the feature vector using the transformation matrix of the feature vector, and updating the acoustic model stored in a memory device using the transformed feature vector, wherein the regularization term controls an amount of change in the transformation matrix relating to a given statistical parameter, the regularization term reduces the amount of change in the transformation matrix relating to the given statistical parameter when the transformation matrix of the feature vector is updated and an amount of training data for the given statistical parameter is less than a threshold amount representative of data sparseness, and the method is performed by an automatic speech recognition system.