A computer-implemented method comprising: receiving, by a computing device, transcriptions of utterances that were received by computing devices operating in a domain and that are in a source language; generating, by the computing device, translated transcriptions of the transcriptions of the utterances in a target language; receiving, by the computing device, a language model for the target language; receiving, by the computing device, additional transcriptions of additional utterances that were received by the computing devices operating in domains other than the domain and that are in the source language; generating, by the computing device, additional translated transcriptions of the additional transcriptions; identifying terms that have a higher appearance frequency in the translated transcriptions than in the additional translated transcriptions; biasing, by the computing device, the language model for the target language by increasing the likelihood of the language model selecting terms included in the translated transcriptions; and generating, by the computing device while operating in the domain, a transcription of an utterance in the target language using the biased language model, wherein biasing the language model for the target language by increasing the likelihood of the language model selecting terms included in the translated transcriptions comprises: biasing the language model for the target language by increasing the likelihood of the language model selecting terms that have a higher appearance frequency in the translated transcriptions than in the additional translated transcriptions. receiving, by a computing device, transcriptions of utterances that were received by computing devices operating in a domain and that are in a source language; generating, by the computing device, translated transcriptions of the transcriptions of the utterances in a target language; receiving, by the computing device, a language model for the target language; receiving, by the computing device, additional transcriptions of additional utterances that were received by the computing devices operating in domains other than the domain and that are in the source language; generating, by the computing device, additional translated transcriptions of the additional transcriptions; identifying terms that have a higher appearance frequency in the translated transcriptions than in the additional translated transcriptions; biasing, by the computing device, the language model for the target language by increasing the likelihood of the language model selecting terms included in the translated transcriptions; and generating, by the computing device while operating in the domain, a transcription of an utterance in the target language using the biased language model, wherein biasing the language model for the target language by increasing the likelihood of the language model selecting terms included in the translated transcriptions comprises: biasing the language model for the target language by increasing the likelihood of the language model selecting terms that have a higher appearance frequency in the translated transcriptions than in the additional translated transcriptions. <EOS>