12. One or more non-transitory computer readable media comprising executable code that, when executed, cause one or more computing devices to perform a process comprising: obtaining catalog information associated with a user profile; generating a personal language model based at least on the catalog information, wherein the personal language model is specific to the user profile, wherein the personal language model includes a first subset of items in a general language model, and wherein the general language model is not associated with any specific user profile; determining, based at least on the catalog information, predicted natural language processing input content, wherein the catalog information does not include the predicted natural language processing input content; generating a predictive language model based at least on the predicted natural language processing input content, wherein the predictive language model is associated with the user profile, and wherein the predictive language model includes a subset of items in the general language model; generating a weighting factor that, when applied to the predictive language model, modifies probabilities associated with at least a portion of items of the predicted natural language processing input content that are determined to be acoustically confusable for at least a portion of items in the general language model; recognizing a first item in a first utterance using the general language model in combination with the personal language model and the predictive language model, wherein the first item is recognized based at least partly on a first probability for the first item being higher than a second probability for a second item and a third probability for a third item, wherein a value of the first probability comprises a product of the weighting factor and a probability value from the personal language model, wherein a value of the second probability comprises a probability value from the predictive language model, and wherein a value of the third probability comprises a probability value from the general language model; and causing audio content associated with the first item to be played by an output device.
12. One or more non-transitory computer readable media comprising executable code that, when executed, cause one or more computing devices to perform a process comprising: obtaining catalog information associated with a user profile; generating a personal language model based at least on the catalog information, wherein the personal language model is specific to the user profile, wherein the personal language model includes a first subset of items in a general language model, and wherein the general language model is not associated with any specific user profile; determining, based at least on the catalog information, predicted natural language processing input content, wherein the catalog information does not include the predicted natural language processing input content; generating a predictive language model based at least on the predicted natural language processing input content, wherein the predictive language model is associated with the user profile, and wherein the predictive language model includes a subset of items in the general language model; generating a weighting factor that, when applied to the predictive language model, modifies probabilities associated with at least a portion of items of the predicted natural language processing input content that are determined to be acoustically confusable for at least a portion of items in the general language model; recognizing a first item in a first utterance using the general language model in combination with the personal language model and the predictive language model, wherein the first item is recognized based at least partly on a first probability for the first item being higher than a second probability for a second item and a third probability for a third item, wherein a value of the first probability comprises a product of the weighting factor and a probability value from the personal language model, wherein a value of the second probability comprises a probability value from the predictive language model, and wherein a value of the third probability comprises a probability value from the general language model; and causing audio content associated with the first item to be played by an output device. 19. The one or more non-transitory computer readable media of claim 12 , the process further comprising multiplying the weighing factor by at least a portion of the probabilities associated with items of the predicted natural language processing input content to generate weighted probabilities, wherein the recognizing the first item in the first utterance comprises recognizing the first item using at least one of the weighted probabilities.