20. A method for knowledge-enhanced speech recognition, comprising: storing one or more expected contexts in a context stack, wherein a knowledge-enhanced speech recognition engine that includes one or more processors accesses the one or more expected contexts in the context stack in response to one or more active grammars in a context description grammar failing to completely match information associated with the natural language utterance; comparing the information associated with the natural language utterance to one or more context specific matchers to determine a most likely context associated with the natural language utterance, wherein the knowledge-enhanced speech recognition engine determines the most likely context from the one or more expected contexts in the context stack; and using one or more grammar expression entries in the context description grammar to generate a command or request associated with the most likely context.
20. A method for knowledge-enhanced speech recognition, comprising: storing one or more expected contexts in a context stack, wherein a knowledge-enhanced speech recognition engine that includes one or more processors accesses the one or more expected contexts in the context stack in response to one or more active grammars in a context description grammar failing to completely match information associated with the natural language utterance; comparing the information associated with the natural language utterance to one or more context specific matchers to determine a most likely context associated with the natural language utterance, wherein the knowledge-enhanced speech recognition engine determines the most likely context from the one or more expected contexts in the context stack; and using one or more grammar expression entries in the context description grammar to generate a command or request associated with the most likely context. 22. The method of claim 20 , wherein the knowledge-enhanced speech recognition engine determines an intent or corrects a recognition associated with the natural language utterance based on the most likely context.