System for using statistical classifiers for spoken language understanding
First Claim
Patent Images
1. A text classifier in a natural language interface that receives a natural language user input, the text classifier comprising:
- a feature extractor extracting a feature vector from a textual input indicative of the natural language user input;
a statistical classifier coupled to the feature extractor outputting a class identifier identifying a target class associated with the textual input based on the feature vector.
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Abstract
The present invention involves using one or more statistical classifiers in order to perform task classification on natural language inputs. In another embodiment, the statistical classifiers can be used in conjunction with a rule-based classifier to perform task classification.
200 Citations
51 Claims
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1. A text classifier in a natural language interface that receives a natural language user input, the text classifier comprising:
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a feature extractor extracting a feature vector from a textual input indicative of the natural language user input;
a statistical classifier coupled to the feature extractor outputting a class identifier identifying a target class associated with the textual input based on the feature vector. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22)
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23. A computer-implemented method of processing a natural language input for use in completing a task represented by the natural language input, comprising:
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performing statistical classification on the natural language input to obtain a class identifier for a target class associated with the natural language input;
identifying rules in a rule-based analyzer based on the class identifier; and
analyzing the natural language input with the rule-based analyzer using the identified rules to fill semantic slots in the target class. - View Dependent Claims (24, 25, 26, 27, 28, 29)
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30. A system for identifying a task to be performed by a computer based on a natural language input, comprising:
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a feature extractor extracting features from the natural language input; and
a statistical classifier, trained to accommodate unseen data, receiving the extracted features and identifying the task based on the features. - View Dependent Claims (31, 32)
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33. A text classifier identifying a target class corresponding to a natural language input, comprising:
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a feature extractor extracting a set of features from the natural language input; and
a Naï
ve Bayes Classifier receiving the set of features and identifying the target class based on the set of features. - View Dependent Claims (34, 35, 36)
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37. A text classifier identifying a target class corresponding to a natural language input, comprising:
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a feature extractor extracting a set of features from the natural language input; and
a statistical language model classifier receiving the set of features and identifying the target class based on the set of features. - View Dependent Claims (38, 39)
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40. A text classifier identifying one or more target classes corresponding to a natural language input, comprising:
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a feature extractor extracting a set of features from the natural language input; and
a plurality of statistical classifiers receiving the set of features and identifying a target class based on the set of features. - View Dependent Claims (41, 42)
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43. A text classifier identifying a target class corresponding to a natural language input, comprising:
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a feature extractor extracting a set of features from the natural language input;
a statistical classifier receiving the set of features and outputting a class identifier based on the set of features;
a rules based classifier outputting a class identifier based on the natural language input; and
a selector selecting a target class based on the class identifiers output by the statistical classifier and the rule-based classifier. - View Dependent Claims (44)
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45. A text classifier identifying a target task to be completed corresponding to a natural language input, comprising:
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a feature extractor extracting a set of features from a textual input indicative of the natural language input;
a statistical classifier receiving the set of features and identifying the target task based on the set of features; and
a rule-based parser receiving the textual input and a class identifier indicative of the identified target task and outputting a semantic representation of the textual input. - View Dependent Claims (46, 47, 48, 49, 50, 51)
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Specification