1. A system comprising: a computer-readable memory storing executable instructions; and one or more processors in communication with the computer-readable memory, wherein the one or more processors are programmed by the executable instructions to at least: obtain item information regarding an item expected to be referenced in user utterances in a future period of time more often than the item was referenced in user utterances in a prior period of time; obtain language use prediction data regarding the item, the language use prediction data associated with one or more previously selected features; determine, using the language use prediction data and a machine learning model trained to generate probabilities based on the one or more previously selected features, a probability that the item will be referenced in user utterances in the future period of time; generate a predictive language model comprising a word in a name of the item and a corresponding probability related to the word, the corresponding probability based at least partly on the determined probability; determine a probability, from a general model, that the name of the item is included in a user utterance; and adjust the probability that the name of the item is included in the user utterance based at least on the corresponding probability indicated in the predictive language model.