Apparatus and method for model adaptation for spoken language understanding
First Claim
Patent Images
1. A method of building a classification model for a target application, comprising:
- obtaining existing labeled data from an existing classification model of a first domain-specific application;
obtaining data labeled for the target application; and
forming, via a processor, a new classification model for use with the target application by using the existing labeled data from the existing classification model and the data labeled for the target application to train the new classification model, the target application being different from the first domain-specific application and in a different domain from the first domain-specific application.
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Abstract
An apparatus and a method are provided for building a spoken language understanding model. Labeled data may be obtained for a target application. A new classification model may be formed for use with the target application by using the labeled data for adaptation of an existing classification model. In some implementations, the existing classification model may be used to determine the most informative examples to label.
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Citations
20 Claims
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1. A method of building a classification model for a target application, comprising:
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obtaining existing labeled data from an existing classification model of a first domain-specific application; obtaining data labeled for the target application; and forming, via a processor, a new classification model for use with the target application by using the existing labeled data from the existing classification model and the data labeled for the target application to train the new classification model, the target application being different from the first domain-specific application and in a different domain from the first domain-specific application. - View Dependent Claims (2, 3, 4, 5, 6)
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7. An apparatus comprising:
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a processor; and storage for storing instructions for the processor, wherein the apparatus is configured to; obtain existing labeled data from an existing classification model of a first domain-specific application; obtain data labeled for a target application; and form a new classification model for use with the target application by using the existing labeled data from the existing classification model and the data labeled for the target application to train the new classification model, the target application being different from the first domain-specific application and in a different domain from the first domain-specific application. - View Dependent Claims (8, 9, 10, 11)
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12. A non-transitory machine-readable medium having instructions, stored therein, for a processor, the machine-readable medium comprises:
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instructions for inputting existing labeled data from an existing classification model of a first domain-specific application; instructions for inputting data labeled for a target application; and instructions for forming a new classification model for use with the target application by using the existing labeled data from the existing classification model and the data labeled for the target application to train the new classification model, the target application being different from the first domain-specific application and in a different domain from the first domain-specific application. - View Dependent Claims (13, 14, 15, 16)
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17. An apparatus comprising:
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means for obtaining existing labeled data from an existing classification model for a first domain-specific application; means for obtained data labeled for a target application; and means for forming a new classification model for use with the target application by using the existing labeled data from the existing classification model and the data labeled for the target application to train the new classification model, the target application being different from the first domain-specific application and in a different domain from the first domain-specific application. - View Dependent Claims (18, 19, 20)
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Specification