TEXT PREDICTION BASED ON MULTIPLE LANGUAGE MODELS

摘要

In one or more implementations, text prediction candidates corresponding to detected text characters are generated according to an adaptive language model. The adaptive language model may be configured to include multiple individual language model dictionaries having respective scoring data that is combined together to rank and select prediction candidates for different interaction scenarios. In addition to a pre-defined general population dictionary, the dictionaries may include a personalized dictionary and/or interaction-specific dictionaries that are learned by monitoring a user's typing activity to adapt predictions to the user's style. Combined probabilities for predictions are then computed as a weighted combination of individual probabilities from multiple dictionaries of the adaptive language model. In an implementation, dictionaries corresponding to multiple different languages may be combined to produce multi-lingual predictions.