12. A system for identifying one or more languages in a document, the system comprising: a language model data store configured to store an n-gram based language model for each of a plurality of languages; a document information data store configured to store information for each of a plurality of documents, the information including language identifying information indicating one or more languages associated with the document; and a processor coupled to the language model data store and the document information data store, the processor being configured to execute language identification processes, the language identification processes including: a first process that, when executed, generates n-gram data for a test document; a second process that, when executed, generates a final score for the test document based on the n-gram data and the n-gram based language model for a candidate language M, wherein the final score is based on relative probabilities of a first hypothesis that the target document is entirely in the candidate language M and a second hypothesis that one portion of the target document is in the candidate language M while another portion of the target document is in an alternative language L wherein the alternative language L does not overlap with the candidate language M; and a third process that, when executed, identifies one or more languages for the test document based on the final scores produced by the second process for each of a plurality of candidate languages.
12. A system for identifying one or more languages in a document, the system comprising: a language model data store configured to store an n-gram based language model for each of a plurality of languages; a document information data store configured to store information for each of a plurality of documents, the information including language identifying information indicating one or more languages associated with the document; and a processor coupled to the language model data store and the document information data store, the processor being configured to execute language identification processes, the language identification processes including: a first process that, when executed, generates n-gram data for a test document; a second process that, when executed, generates a final score for the test document based on the n-gram data and the n-gram based language model for a candidate language M, wherein the final score is based on relative probabilities of a first hypothesis that the target document is entirely in the candidate language M and a second hypothesis that one portion of the target document is in the candidate language M while another portion of the target document is in an alternative language L wherein the alternative language L does not overlap with the candidate language M; and a third process that, when executed, identifies one or more languages for the test document based on the final scores produced by the second process for each of a plurality of candidate languages. 14. The system of claim 12 wherein the n-grams are bigrams.