Abstract: Maintaining dynamic categories for speech rules in a speech recognition system which has a plurality of speech rules each comprising a language model and action. Each speech rule indicates whether the language model includes a flag identifying whether the words in the language model is dynamic according to changing data in the speech recognition system. At periodic intervals, such as system initialization or application program launch time, for each flag in each speech rule which indicates that words in the language model are dynamic, the words of each of the language model(s) are updated depending upon the state of the system. Concurrent with the determination of acoustic features during speech recognition, a current language model can be created based upon the language models from these speech rules.

Abstract: Partitioning speech recognition rules for generation of a current language model and interpretation in a speech recognition system. Contexts for each of speech recognition rules are determined when each of the speech rules will be active. At one interval (e.g. initialization of the system), common contexts for the speech rules are determined and grouped or partitioned into speech rule sets according to these common contexts. Rapid and efficient generation of a language model upon the detection of a current context at a second interval (e.g. upon the detection of speech in one embodiment) then may be performed. Subsequent to the generation of the language model, interpretation may be performed using the speech recognition rules grouped into these common contexts.

Abstract: A method of speech recognition which determines acoustic features in a sound sample; recognizes words comprising the acoustic features based on a language model, which determines the possible sequences of words that may be recognized; and the selection of an appropriate response based on the words recognized. Information about what words may be recognized, under which conditions those words may be recognized, and what response is appropriate when the words are recognized, is stored, in a preferred embodiment, in a data structure called a speech rule. These speech rules are partitioned according to the context in which they are active. When speech is detected, concurrent with acoustic feature extraction, the current state of the computer system is used to determine which rules are active and how they are to be combined in order to generate a language model for word recognition. A language model is dynamically generated and used to find the best interpretation of the acoustic features as a word sequence.