1. A computer-implemented method for generating training data for call routing, the computer-implemented method comprising: accessing a first text corpus, the first text corpus including transcribed utterances that have been transcribed from spoken queries spoken in a first natural language, each transcribed utterance linked to a semantic tag that a first speech recognition call router uses to route telephone calls; translating the transcribed utterances from the first natural language to a second natural language via a machine translation process, the machine translation process generating an N-best list of possible translations for each transcribed utterance that is processed by the machine translation process, each possible translation having a machine translation score that indicates a probability of being a correct translation, each possible translation being linked to a semantic tag from a corresponding transcribed utterance; from each N-best list, selecting a 1-best possible translation and adding the 1-best translation to a second text corpus, each selected 1-best translation having a highest machine translation score as compared to machine translation scores of other possible translations within a respective N-best list; from each N-best list, selecting a second possible translation and adding the second possible translation to the second text corpus, each selected second possible translation being selected based on a measure of individual words from each possible translation that match individual words from at least one possible translation that has been added to the second text corpus and that has been selected from a same N-best list; and training a second speech recognition call router using the second text corpus, the second speech recognition call router configured to recognize spoken queries that are spoken in the second natural language, the second speech recognition call router using a speech classification system based on the first speech recognition call router.