Semantic re-ranking of NLU results in conversational dialogue applications
First Claim
1. A method, comprising:
- generating, by at least one processor of a computing platform comprising the at least one processor and a memory, a plurality of natural language understanding (NLU) interpretation selection models that includes a generic NLU interpretation selection model that is not specialized for a specific set of NLU interpretations type, a first specialized NLU interpretation selection model specific to a first set of NLU interpretations type, and a second specialized NLU interpretation selection model, the second specialized NLU interpretation selection model being specific to a second set of NLU interpretations type, the second set of NLU interpretations type being different from the first set of NLU interpretations type;
receiving natural language input data comprising;
a first data portion comprising sets of NLU interpretations types corresponding to the first set of NLU interpretations type,a second data portion comprising sets of NLU interpretations types corresponding to the second set of NLU interpretations type, anda third data portion;
parsing the natural language input data to identify the first data portion and the second data portion;
identifying a remainder of the natural language input data as the third data portion;
processing, by the at least one processor, the first data portion using the first specialized NLU interpretation selection model;
processing, by the at least one processor, the second data portion using the second specialized NLU interpretation selection model; and
processing, by the at least one processor, the third data portion using the generic NLU interpretation selection model.
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Accused Products
Abstract
Multiple natural language understanding (NLU) interpretation selection models may be generated. The NLU interpretation selection models may include a generic NLU interpretation selection model that is not specialized for a specific set of NLU interpretations type and one or more specialized NLU interpretation selection models, each of which may be specific to a particular set of NLU interpretations type. The specialized NLU interpretation selection model(s) may be utilized to process natural language input data comprising data corresponding to their respective sets of NLU interpretations type(s). The generic NLU interpretation selection model may be utilized to process natural language input data comprising data that does not correspond to the sets of NLU interpretations type(s) associated with the specialized NLU interpretation selection model(s).
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Citations
20 Claims
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1. A method, comprising:
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generating, by at least one processor of a computing platform comprising the at least one processor and a memory, a plurality of natural language understanding (NLU) interpretation selection models that includes a generic NLU interpretation selection model that is not specialized for a specific set of NLU interpretations type, a first specialized NLU interpretation selection model specific to a first set of NLU interpretations type, and a second specialized NLU interpretation selection model, the second specialized NLU interpretation selection model being specific to a second set of NLU interpretations type, the second set of NLU interpretations type being different from the first set of NLU interpretations type; receiving natural language input data comprising; a first data portion comprising sets of NLU interpretations types corresponding to the first set of NLU interpretations type, a second data portion comprising sets of NLU interpretations types corresponding to the second set of NLU interpretations type, and a third data portion; parsing the natural language input data to identify the first data portion and the second data portion; identifying a remainder of the natural language input data as the third data portion; processing, by the at least one processor, the first data portion using the first specialized NLU interpretation selection model; processing, by the at least one processor, the second data portion using the second specialized NLU interpretation selection model; and processing, by the at least one processor, the third data portion using the generic NLU interpretation selection model. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10)
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11. An apparatus, comprising:
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at least one processor; and a memory storing instructions that when executed by the at least one processor cause the apparatus to; generate a generic NLU interpretation selection model that is not specialized for a specific set of NLU interpretations type; generate a first specialized NLU interpretation selection model specific to a first set of NLU interpretations type; generate a second specialized NLU interpretation selection model, the second specialized NLU interpretation selection model being specific to a second set of NLU interpretations type, the second set of NLU interpretations type being different from the first set of NLU interpretations type; receive natural language input data comprising; a first data portion comprising sets of NLU interpretations types corresponding to the first set of NLU interpretations type, a second data portion comprising sets of NLU interpretations types corresponding to the second set of NLU interpretations type, and a third data portion; parse the natural language input data to identify the first data portion and the second data portion; identify a remainder of the natural language input data as the third data portion; process the first data portion using the first specialized NLU interpretation selection model; process the second data portion using the second specialized NLU interpretation selection model; and process the third data portion using the generic NLU interpretation selection model. - View Dependent Claims (12, 13, 14, 15)
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16. One or more non-transitory computer-readable media having instructions stored thereon that when executed by one or more computers cause the one or more computers to:
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generate a generic NLU interpretation selection model that is not specialized for a specific set of NLU interpretations type; generate a first specialized NLU interpretation selection model specific to a first set of NLU interpretations type; generate a second specialized NLU interpretation selection model, the second specialized NLU interpretation selection model being specific to a second set of NLU interpretations type, the second set of NLU interpretations type being different from the first set of NLU interpretations type; receive natural language input data comprising; a first data portion comprising sets of NLU interpretations types corresponding to the first set of NLU interpretations type, a second data portion comprising sets of NLU interpretations types corresponding to the second set of NLU interpretations type, and a third data portion; parse the natural language input data to identify the first data portion and the second data portion; identify a remainder of the natural language input data as the third data portion; process the first data portion using the first specialized NLU interpretation selection model; process the second data portion using the second specialized NLU interpretation selection model; and process the third data portion using the generic NLU interpretation selection model. - View Dependent Claims (17, 18, 19, 20)
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Specification