18. The method of claim 16 , wherein the at least one domain-specific feature comprises an out of vocabulary word feature which, for a candidate translation, is based on a number of terms in the candidate translation that are not present within the domain-specific corpus, where each of the terms comprises a word of the candidate translation or a lemma form thereof.
16. A domain-specific translation method comprising: receiving an input query in a source language; with a machine translation system that is not adapted to a specific domain, translating the query to generate a set of candidate translations of the query in a target language; extracting a set of features from each of the candidate translations in the set, the set of features including at least one domain specific feature which is based on a comparison of at least one term in the candidate translation with words in an associated domain-specific corpus of documents in the target language; scoring each of the candidate translations with a scoring function in which the extracted features are weighted with respective weights, the weights having been learned on features extracted from translated queries, each generated by translation of an original query into the target language, and a measure of information retrieval performance of each the translated queries for each original query in a set of original queries, the information retrieval performance being assessed on a domain-specific target document collection in which documents in the collection are annotated based on relevance to the original queries; and outputting a target query based on the scores of the candidate translations, wherein the at least one domain-specific feature is selected from the group consisting of: a) a language model feature; b) an out of vocabulary word feature; c) a query performance predictor which is computed with an equation that correlates with the measure of information retrieval performance; and combinations thereof.