1. A computer-implemented method comprising: receiving a document from a server, the document including at least one tag associated with a first portion of text within the document; receiving a request from a user to translate the document from a first language to a second language, the second language being different than the first language; providing the document to a human translator; receiving a manual translation of the document from the human translator, the manual translation being a version of the document that has been translated from the first language into the second language by the human translator and that does not include the at least one tag; generating a plurality of alignments between the document and the manual translation of the document using a hidden Markov model and at least one other statistical alignment model, each of the plurality of alignments associating the first portion of text within the document with a second portion of text within the manual translation of the document; generating a probability score for each of the plurality of alignments using a translation corpus and a machine learning routine, the probability score for a specific alignment indicating a likelihood that the first portion of text within the document corresponds to the associated second portion of text in the manual translation of the document according to the specific alignment; selecting one of the plurality of alignments as a selected alignment based on the plurality of probability scores, the selected alignment having a highest corresponding probability score; mapping a location of the at least one tag in the document to a corresponding location within the manual translation based on the selected alignment; inserting the at least one tag into the manual translation at the corresponding location to obtain a modified manual translation of the document; and providing the modified manual translation of the document to the user.