1. A method comprising: obtaining, at a computing system, respective word frequencies f i from a corpus of utterance-to-text-string mappings, wherein the corpus of utterance-to-text-string mappings contains associations between audio utterances and respective text string transcriptions of the audio utterances, and wherein the respective word frequencies f i are based on occurrences of words in the text string transcriptions; determining respective compressed word frequencies c i by raising each of the respective word frequencies f i to a power m, wherein m<1 and c i =f i m ; selecting sample utterance-to-text-string mappings from the corpus of utterance-to-text-string mappings based on the respective compressed word frequencies c i ; and training an automatic speech recognition (ASR) system with the sample utterance-to-text-string mappings.
1. A method comprising: obtaining, at a computing system, respective word frequencies f i from a corpus of utterance-to-text-string mappings, wherein the corpus of utterance-to-text-string mappings contains associations between audio utterances and respective text string transcriptions of the audio utterances, and wherein the respective word frequencies f i are based on occurrences of words in the text string transcriptions; determining respective compressed word frequencies c i by raising each of the respective word frequencies f i to a power m, wherein m<1 and c i =f i m ; selecting sample utterance-to-text-string mappings from the corpus of utterance-to-text-string mappings based on the respective compressed word frequencies c i ; and training an automatic speech recognition (ASR) system with the sample utterance-to-text-string mappings. 9. The method of claim 1 , further comprising: before training the ASR system with the sample utterance-to-text-string mappings, training the ASR system with the entire corpus of utterance-to-text-string mappings.