A computer-implemented method comprising: receiving, by an automated speech recognizer, audio data corresponding to an utterance of a user (102, 310), receiving, by a candidate transcription expander, data indicating a location associated with the user (102, 310); obtaining, by the automated speech recognizer, an initial candidate transcription (104c, 320) 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 (104c, 320) 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 (104c, 320), and that are indicated as phonetically similar to one or more terms that do occur in the initial candidate transcription (104c, 320); selecting, by the automated speech recognizer, from among the initial candidate transcription (104c, 320) 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 (110, 360). receiving, by an automated speech recognizer, audio data corresponding to an utterance of a user (102, 310), receiving, by a candidate transcription expander, data indicating a location associated with the user (102, 310); obtaining, by the automated speech recognizer, an initial candidate transcription (104c, 320) 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 (104c, 320) 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 (104c, 320), and that are indicated as phonetically similar to one or more terms that do occur in the initial candidate transcription (104c, 320); selecting, by the automated speech recognizer, from among the initial candidate transcription (104c, 320) 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 (110, 360).