1. A method performed by one or more computers, the method comprising: receiving data indicating a candidate transcription for an utterance and a particular context for the utterance; obtaining a maximum entropy language model that includes (i) scores for one or more n-gram features that each correspond to a respective n-gram and (ii) scores for one or more backoff features that each correspond to a set of n-grams for which there are no corresponding n-gram features in the maximum entropy language model; determining, based on the candidate transcription and the particular context, a feature value for (i) each of the one or more n-gram features of the maximum entropy language model and (ii) each of the one or more backoff features of the maximum entropy language model; inputting the feature values for the n-gram features and the feature values for the backoff features to the maximum entropy language model; and receiving, from the maximum entropy language model, an output indicative of a likelihood of occurrence of the candidate transcription; selecting, based on the output of the maximum entropy language model, a transcription for the utterance from among a plurality of candidate transcriptions; and providing the selected transcription to a client device.