2. A method performed by one or more computers of an automated speech recognition system, the method comprising: using, by the one or more computers of the automated speech recognition system, a first set of multiple mappings between phoneme sequences and words to determine a first word-level transcription for a particular utterance spoken by a particular speaker, the first word-level transcription including a first set of one or more words; using, by the one or more computers of the automated speech recognition system, a second set of multiple mappings between phoneme sequences and words to determine a second word-level transcription for the particular utterance spoken by the particular speaker, wherein the first word-level transcription and the second word-level transcription are transcriptions of the same particular utterance spoken by the same particular speaker, wherein the second word-level transcription includes a second set of one or more words that is different from the first set of one or more words, and wherein the second set of multiple mappings is different from the first set of multiple mappings; determining, by the one or more computers of the automated speech recognition system, that the second set of one or more words of the second word-level transcription includes a word that is different from the first set of one or more words of the first word-level transcription and in response to the determination: identifying, by the one or more computers of the automated speech recognition system, a mapping in the second set of multiple mappings that causes the second set of one or more words of the second word-level transcription to be different from the first set of one or more words of the first word-level transcription; determining, by the one or more computers of the automated speech recognition system, feature scores based on the first word-level transcription and the second word-level transcription, wherein the feature scores include (i) a first measure of frame alignment between the first word-level transcription and an audio waveform of the particular utterance, (ii) a second measure of frame alignment between the second word-level transcription and the particular utterance, and (iii) data indicating a difference between a length of the first word-level transcription and a length of the second word-level transcription; and providing the feature scores to a classifier; receiving, by the one or more computers of the automated speech recognition system, an output of the classifier generated using the feature scores, the output of the classifier indicating that the first word-level transcription is more likely to be a correct transcription of the particular utterance spoken by the particular speaker than the second word-level transcription; and in response to receiving the output, providing, by the one or more computers of the automated speech recognition system and as an output of the automated speech recognition system, a transcription determined (i) using the first set of multiple mappings between phoneme sequences and words and (ii) not using the second set of multiple mappings between phoneme sequences and words.
9. The method of claim 2 , wherein determining feature scores based on the first word-level transcription and the second word-level transcription comprises obtaining data specifying whether the second word-level transcription has been provided as a suggested query in response to receiving a query that matches the first word-level transcription.