12. A non-transitory computer storage medium encoded with instructions that, when executed by a device, cause the device to perform operations comprising: receiving, by the device, a set of development sentences W; receiving a set of two or more language models G M , each language model in the set of two or more language models G M for use by an automatic speech recognition system when generating text from speech; determining a set of n-gram language model weights λ M using the development sentences W and the set of two or more language models G M ; determining a set of sentence cluster weights γ C , each of the sentence cluster weights corresponding to a cluster in a set of sentence clusters, each cluster in the set of sentence clusters associated with at least one sentence from the set of development sentences W; generating a language model from the set of two or more language models G M , the set of n-gram language model weights λ M , the set of sentence clusters, and the set of sentence cluster weights γ C ; and providing, by the device, the language model for use by an automatic speech recognition system to determine n-grams included in an utterance encoded in an audio signal.
12. A non-transitory computer storage medium encoded with instructions that, when executed by a device, cause the device to perform operations comprising: receiving, by the device, a set of development sentences W; receiving a set of two or more language models G M , each language model in the set of two or more language models G M for use by an automatic speech recognition system when generating text from speech; determining a set of n-gram language model weights λ M using the development sentences W and the set of two or more language models G M ; determining a set of sentence cluster weights γ C , each of the sentence cluster weights corresponding to a cluster in a set of sentence clusters, each cluster in the set of sentence clusters associated with at least one sentence from the set of development sentences W; generating a language model from the set of two or more language models G M , the set of n-gram language model weights λ M , the set of sentence clusters, and the set of sentence cluster weights γ C ; and providing, by the device, the language model for use by an automatic speech recognition system to determine n-grams included in an utterance encoded in an audio signal. 13. The computer storage medium of claim 12 , the operations further comprising: determining, for each sentence in the set of development sentences W, a probability p of the sentence using the set of n-gram language model weights λ M , and the set of sentence cluster weights γ C .