A method, comprising: detecting (502; 702) entry of text characters during interaction with a device; generating (504; 704) one or more text prediction candidates corresponding to the detected text characters according to an adaptive language model by: identifying multiple dictionaries of the adaptive language model as sources of word candidates for the text prediction candidates based on the detected text characters; computing, for each text prediction candidate, a weighted combination of scoring data associated with word candidates contained in multiple dictionaries of the adaptive language model, wherein the weighted combination of scoring data for each text prediction candidate is computed by summing the scoring data for the word candidates output by each of the multiple dictionaries adjusted by weight factors dynamically generated for each of the word candidates; ranking the text prediction candidates one to another based on the computed weighted combination of scoring data for each text prediction candidate; and employing (506; 706-708) the one or more text prediction candidates to facilitate further text entry for the interaction with the device. detecting (502; 702) entry of text characters during interaction with a device; generating (504; 704) one or more text prediction candidates corresponding to the detected text characters according to an adaptive language model by: identifying multiple dictionaries of the adaptive language model as sources of word candidates for the text prediction candidates based on the detected text characters; computing, for each text prediction candidate, a weighted combination of scoring data associated with word candidates contained in multiple dictionaries of the adaptive language model, wherein the weighted combination of scoring data for each text prediction candidate is computed by summing the scoring data for the word candidates output by each of the multiple dictionaries adjusted by weight factors dynamically generated for each of the word candidates; ranking the text prediction candidates one to another based on the computed weighted combination of scoring data for each text prediction candidate; and employing (506; 706-708) the one or more text prediction candidates to facilitate further text entry for the interaction with the device. identifying multiple dictionaries of the adaptive language model as sources of word candidates for the text prediction candidates based on the detected text characters; computing, for each text prediction candidate, a weighted combination of scoring data associated with word candidates contained in multiple dictionaries of the adaptive language model, wherein the weighted combination of scoring data for each text prediction candidate is computed by summing the scoring data for the word candidates output by each of the multiple dictionaries adjusted by weight factors dynamically generated for each of the word candidates; ranking the text prediction candidates one to another based on the computed weighted combination of scoring data for each text prediction candidate; and employing (506; 706-708) the one or more text prediction candidates to facilitate further text entry for the interaction with the device.