Abstract: A method of modeling a speech recognition system includes decoding a speech signal produced from a training text to produce a sequence of predicted speech units. The training text comprises a sequence of actual speech units that is used with the sequence of predicted speech units to form a confusion model. In further embodiments, the confusion model is used to decode a text to identify an error rate that would be expected if the speech recognition system decoded speech based on the text.

Abstract: A method and apparatus are provided for optimizing finite state machines with labeled nodes. Under the method, labels from the nodes are shifted onto the labels of the links connected to the nodes. The finite state machine is then optimized. After optimization, the labels on the links are examined to verify that the prefixes of the labels on each outgoing link match the suffixes of the labels on each incoming link to a particular node. After this verification, a portion of a label on a link is removed from the link and inserted onto the node.

Abstract: A method and apparatus are provided for optimizing finite state machines with labeled nodes. Under the method, labels from the nodes are shifted onto the labels of the links connected to the nodes. The finite state machine is then optimized. After optimization, the labels on the links are examined to verify that the prefixes of the labels on each outgoing link match the suffixes of the labels on each incoming link to a particular node. After this verification, a portion of a label on a link is removed from the link and inserted onto the node.