1. A method performed by one or more computers of an automated speech recognition system, the method comprising: receiving data indicating a candidate transcription for an utterance and a particular context for the utterance; accessing a language model of the automated speech recognition system, the language model including a respective score for each of a plurality of features, each feature corresponding to a word or phrase occurring in an associated context that includes one or more preceding words, wherein the automated speech recognition system is configured to obtain a score for a feature such that: (i) if the language model includes a score for the feature, the one or more computers retrieve the score for the feature that is included in the language model, and (ii) if the language model does not include a score for the feature, the one or more computers obtain a score for the feature that is based on scores for other features associated with a same context as the feature; determining that the language model does not include a score for a feature corresponding to the candidate transcription in the particular context; in response to determining that the language model does not include a score for a feature corresponding to the candidate transcription in the particular context, operating the automated speech recognition system to obtain a score corresponding to the candidate transcription in the particular context, wherein the score is determined based on one or more scores included in the language model for one or more of the plurality of features that are associated with the particular context; determining, using the language model and the determined score, a probability score indicating a likelihood of occurrence of the candidate transcription in the particular context; selecting, based on the probability score, a transcription for the utterance from among a plurality of candidate transcriptions; and providing the selected transcription to a client device as output of the automated speech recognition system.
1. A method performed by one or more computers of an automated speech recognition system, the method comprising: receiving data indicating a candidate transcription for an utterance and a particular context for the utterance; accessing a language model of the automated speech recognition system, the language model including a respective score for each of a plurality of features, each feature corresponding to a word or phrase occurring in an associated context that includes one or more preceding words, wherein the automated speech recognition system is configured to obtain a score for a feature such that: (i) if the language model includes a score for the feature, the one or more computers retrieve the score for the feature that is included in the language model, and (ii) if the language model does not include a score for the feature, the one or more computers obtain a score for the feature that is based on scores for other features associated with a same context as the feature; determining that the language model does not include a score for a feature corresponding to the candidate transcription in the particular context; in response to determining that the language model does not include a score for a feature corresponding to the candidate transcription in the particular context, operating the automated speech recognition system to obtain a score corresponding to the candidate transcription in the particular context, wherein the score is determined based on one or more scores included in the language model for one or more of the plurality of features that are associated with the particular context; determining, using the language model and the determined score, a probability score indicating a likelihood of occurrence of the candidate transcription in the particular context; selecting, based on the probability score, a transcription for the utterance from among a plurality of candidate transcriptions; and providing the selected transcription to a client device as output of the automated speech recognition system. 14. The method of claim 1 , further comprising: pre-computing a minimum score for each of multiple contexts while training the language model; and normalizing scores for features in the language model using the pre-computed minimum scores.