Abstract: The invention relates to a method and apparatus for generating noise-attenuated feature vectors for use in recognizing speech, more particularly to a system and method providing a feature set for speech recognition that is robust to adverse noise conditions. This is done by receiving, through an input, a set of signal frames, at least some containing speech sounds, and then classifying the frames in the set of signal frames into classification groups on the basis of their energy levels. Each classification group is characterized by a mean energy value. In a specific example of implementation, the invention makes use of channel energy values to condition the frames in the set of signal frames. The frames in the set of signal frames are attenuated or noise reduced by altering the energy of the frames on the basis of the frames containing non-speech sounds.

Abstract: Methods and systems consistent with the present invention enroll a candidate phrase uttered by a user in a dictionary having at least one previously enrolled phrase. The system receives utterances of the candidate phrase and determines whether the first utterance is confusingly similar to a previously enrolled phrase and whether they are consistent with each other. The system then enrolls the candidate phrase in the dictionary according to these determinations.