1. A method of generating language models for speech recognition comprising: identifying a plurality of utterances in training data corresponding to speech; generating a frequency count of each utterance in the plurality of utterances; generating a high-frequency plurality of utterances from the plurality of utterances having a frequency that exceeds a predetermined frequency threshold; generating a low-frequency plurality of utterances from the plurality of utterances having a frequency that is below the predetermined frequency threshold; generating with at least one processor a grammar-based language model using the high-frequency plurality of utterances as training data; storing the grammar based language model in a memory; generating with the at least one processor a statistical language model using the low-frequency plurality of utterances as training data; and storing the statistical language model in the memory.
1. A method of generating language models for speech recognition comprising: identifying a plurality of utterances in training data corresponding to speech; generating a frequency count of each utterance in the plurality of utterances; generating a high-frequency plurality of utterances from the plurality of utterances having a frequency that exceeds a predetermined frequency threshold; generating a low-frequency plurality of utterances from the plurality of utterances having a frequency that is below the predetermined frequency threshold; generating with at least one processor a grammar-based language model using the high-frequency plurality of utterances as training data; storing the grammar based language model in a memory; generating with the at least one processor a statistical language model using the low-frequency plurality of utterances as training data; and storing the statistical language model in the memory. 4. The method of claim 1 , further comprising: performing a plurality of speech recognition experiments with the grammar-based language model; identifying a performance of the grammar-based language model in the speech recognition experiments by executing with the at least one processor program instructions stored in the memory; performing the plurality of speech recognition experiments with the statistical language model; identifying a performance of the statistical language model in the speech recognition experiments by executing with the at least one processor the program instructions stored in the memory; and increasing the predetermined frequency threshold when the performance of the grammar-based language model is below a predetermined performance threshold and the performance of the statistical language model is below another predetermined performance threshold.