A computer-implemented method comprising: receiving, by an automated speech recognizer, audio data corresponding to an utterance of a user , receiving, by a candidate transcription expander, data indicating a location associated with the user ; obtaining, by the automated speech recognizer, an initial candidate transcription of the utterance using an acoustic model and a baseline language model, the baseline language model including n-grams; selecting, by a model selector of the candidate transcription expander, for each of multiple geographic regions that are associated with the location, a set of n-grams that are associated with a region; for one or more of the multiple geographic regions, generating, by a transcription generator of the candidate transcription expander, one or more additional candidate transcriptions based on (i) the initial candidate transcription, and (ii) one or more terms of the set of n-grams that are associated with the region, that do not occur in the initial candidate transcription , and that are indicated as phonetically similar to one or more terms that do occur in the initial candidate transcription ; selecting, by the automated speech recognizer, from among the initial candidate transcription and the one or more additional candidate transcriptions , a representative transcription of the utterance, the representative transcription being based on a biasing of the baseline language model by a language model biaser, the baseline language model being positively biased by n-grams included within the additional candidate transcriptions that increase respective probabilities associated with the n-grams included within the additional candidate transcriptions ; and outputting the representative transcription by the automated speech recognizer . receiving, by an automated speech recognizer, audio data corresponding to an utterance of a user , receiving, by a candidate transcription expander, data indicating a location associated with the user ; obtaining, by the automated speech recognizer, an initial candidate transcription of the utterance using an acoustic model and a baseline language model, the baseline language model including n-grams; selecting, by a model selector of the candidate transcription expander, for each of multiple geographic regions that are associated with the location, a set of n-grams that are associated with a region; for one or more of the multiple geographic regions, generating, by a transcription generator of the candidate transcription expander, one or more additional candidate transcriptions based on (i) the initial candidate transcription, and (ii) one or more terms of the set of n-grams that are associated with the region, that do not occur in the initial candidate transcription , and that are indicated as phonetically similar to one or more terms that do occur in the initial candidate transcription ; selecting, by the automated speech recognizer, from among the initial candidate transcription and the one or more additional candidate transcriptions , a representative transcription of the utterance, the representative transcription being based on a biasing of the baseline language model by a language model biaser, the baseline language model being positively biased by n-grams included within the additional candidate transcriptions that increase respective probabilities associated with the n-grams included within the additional candidate transcriptions ; and outputting the representative transcription by the automated speech recognizer . <EOS>