16. The computer-readable medium of claim 15 , wherein: the obtained one or more sources of potential translation pairs comprise single content items that contain multiple languages; each of the at least two language snippets for each potential translation pair is a portion of one of the single content items; each of the at least two language snippets for each potential translation pair comprises two or more consecutive words for which a particular language has been identified; and applying the one of the or more automated filtering techniques comprises eliminating from consideration an unlikely potential translation pair of the one or more potential translation pairs by: determining a first count of terms in a first of the at least two language snippets of the unlikely potential translation pair; determining a second count of terms in a second of the at least two language snippets of the unlikely potential translation pair; computing that a ratio of terms between the first count of terms and the second count of terms is beyond a specified threshold value; and in response to the computing that the ratio of terms is beyond the specified threshold value, eliminating from consideration the unlikely potential translation pair.
15. A non-transitory computer-readable medium storing instructions that, when executed by a computing system, cause the computing system to perform operations for mining translation pairs for training in-domain machine translation engines, the operations comprising: obtaining one or more sources of potential translation pairs comprising one or more content items, wherein the one or more sources of potential translation pairs are in an identified domain for which a machine translation engine is to be trained; generating one or more potential translation pairs from the obtained one or more sources of potential translation pairs by applying one or more automated filtering techniques to the obtained one or more sources of potential translation pairs, wherein one of the one or more automated filtering techniques applied to a selected obtained source of potential translation pairs is configured based on a type of the selected obtained source of potential translation pairs, and wherein each of the one or more potential translation pairs comprises at least two language snippets; selecting at least one actual translation pair from the generated one or more potential translation pairs, said selecting comprising: extracting characteristics from each of the two language snippets of at least one of the one or more potential translation pairs; determining that the two language snippets of the at least one of the one or more potential translation pairs are translations of each other by comparing the extracted characteristics; and training the machine translation engine using the selected at least one actual translation pair.