1. A method for generating a language processing model, comprising: obtaining one or more multi-media labels, wherein each multi-media label is based on a corresponding multi-media item that is associated with a content item, wherein each particular multi-media label is associated with one or more n-grams from the content item that is associated with the multi-media item that corresponds to the particular multi-media label, and wherein an n-gram is a digital representation of one or more words or groups of characters; including, in a language corpus, the one or more n-grams associated with each of the one or more multi-media labels; and generating the language processing model comprising a probability distribution by computing, for each selected n-gram of multiple n-grams in the language corpus, a frequency that the selected n-gram occurs in the language corpus, wherein one or more of the probabilities provided by the probability distribution are multi-media context probabilities indicating a probability of a chosen n-gram occurring, given that the chosen n-gram is associated with provided one or more multi-media labels, wherein the multi-media context probabilities are based on the associations between the one or more multi-media labels and the one or more n-grams.