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Abstract

A method and apparatus are provided for automatically recognizing words of spoken speech using a computer-based speech recognition system according to a dynamic semantic model. In an embodiment, the speech recognition system recognizes speech and generates one or more word strings, each of which is a hypothesis of the speech, and creates and stores a probability value or score for each of the word strings. The word strings are ordered by probability value. The speech recognition system also creates and stores, for each of the word strings, one or more keyword-value pairs that represent semantic elements and semantic values of the semantic elements for the speech that was spoken. One or more dynamic semantic rules are defined that specify how a probability value of a word string should be modified based on information about external conditions, facts, or the environment of the application in relation to the semantic values of that word string. A speech recognition application, upon receiving the keyword-value pairs, instructs the speech recognizer to modify one or more of the probability values, according to the dynamic semantic rules. The dynamic semantic rules are applied to the word strings and the keyword-value pairs. The speech recognizer modifies one or more of the probability values, re-orders the word strings, and returns control to the application. As a result, the speech recognizer may adjust dynamically to a changing likelihood that a speaker uttered a particular utterance, as the application executes, depending on the context of the application and the external factors.

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First Claim