System and method for inputting text into electronic devices based on text and text category predictions
First Claim
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1. A system for generating text input, the system comprising:
- a processor; and
memory storing instructions that, when executed by the processor, configure the processor to;
receive a text input;
generate, using at least two predictors, a plurality of text predictions from each predictor based on the text input, wherein each of the plurality of text predictions is a word or phrase mapped to a probability value;
generate, using a classifier, at least two text category predictions based on the text input, wherein each text category prediction comprises a category mapped to a probability value;
weight, using a weighting module, the probabilities of the plurality of text predictions from each predictor by the probability of a corresponding category prediction to generate a plurality of category-weighted text predictions;
determine the n most probable category-weighted text predictions; and
output the n most probable category-weighted text predictions for presentation to a user.
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Abstract
The present invention relates generally to a system and method for text prediction and, in particular, a system and method for the adaptive weighting of text predictions. The present invention provides a modular language model-based text prediction system for the adaptive weighting of text prediction components and a method for doing so. The system uses category predictions, generated by a timed aggregated perceptron classifier, to weight, using a weighting module, text predictions generated by a text prediction engine comprising at least one predictor.
221 Citations
19 Claims
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1. A system for generating text input, the system comprising:
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a processor; and memory storing instructions that, when executed by the processor, configure the processor to; receive a text input; generate, using at least two predictors, a plurality of text predictions from each predictor based on the text input, wherein each of the plurality of text predictions is a word or phrase mapped to a probability value; generate, using a classifier, at least two text category predictions based on the text input, wherein each text category prediction comprises a category mapped to a probability value; weight, using a weighting module, the probabilities of the plurality of text predictions from each predictor by the probability of a corresponding category prediction to generate a plurality of category-weighted text predictions; determine the n most probable category-weighted text predictions; and output the n most probable category-weighted text predictions for presentation to a user. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10)
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11. A method of generating text predictions, comprising;
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receiving a text input; generating using at least two predictors a plurality of the text predictions from each predictor based upon the text input, wherein each of the plurality of text predictions is a word or phrase mapped to a probability value; generating, using a classifier, at least two text category predictions based on the text input and a feature vector for a category, wherein each text category prediction comprises a category mapped to a probability value; weighting the probabilities of the plurality of text predictions from each predictor by the probability of a corresponding text category prediction to generate a plurality of category-weighted text predictions; determining the n most probable category-weighted text predictions; and outputting the n most probable category-weighted text predictions. - View Dependent Claims (12, 13, 14, 15, 16, 17, 18, 19)
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Specification