Abstract: Enrolling a user in a speech recognition system includes analyzing acoustic content of a user utterance and determining whether the utterance matches a portion of an enrollment text. If the user utterance matches a portion of the enrollment text, the acoustic content is used to update acoustic models corresponding to the portion of the enrollment text.

Abstract: A computerized system time aligns frames of spoken training data against models of the speech sounds; automatically selects different sets of phonetic context classifications which divide the speech sound models into speech sound groups aligned against acoustically similar frames; creates model components from the frames aligned against speech sound groups with related classifications; and uses these model components to build a separate model for each related speech sound group. A decision tree classifies speech sounds into such groups, and related speech sound groups descend from common tree nodes. New speech samples time aligned against a given speech sound group's model update models of related speech sound groups, decreasing the training data required to adapt the system. The phonetic context classifications can be based on knowledge of which contextual features are associated with acoustic similarity.