IP Library › Granted Patent US 10,380,261
Granted Patent B2
US 10,380,261 · App. 15/852,552 · Granted Aug 13, 2019

Conversational language and informational response systems and methods

Inventor: Erika Varis Doggett (Burbank, CA)
Assignee: Disney Enterprises, Inc.
G06F17/2785G06F16/3329G06F16/3344G06F16/353G06F17/2705G06F17/277G10L15/1815G10L15/1822G10L15/22
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Quick Facts
Patent No.
US 10,380,261
App. No.
15/852,552
Granted
Aug 13, 2019
Kind
B2
Abstract

Systems and methods for a computer-based, interactive communications system capable of generating a response to a human language input are provided. The computer-based, interactive communications systems includes a plurality of response models that may be selected to process one or more keywords extracted from the human language input. The plurality of response models may include at least one conversational response model and at least one informational response model, so that the computer-based, interactive communications system is able to respond to the human language input in a manner commensurate with the type of human language input it receives.

Claims (33)

1. A computer-implemented method, comprising:

receiving a language input;

parsing the language input into one or more token segments;

classifying the token segments according to a response model for suitably generating a response to the token segments;

determining whether the classification is suitable;

processing the token segments through one or more response models upon a determination that the classification is suitable;

determining whether a proposed response generated by the one or more response models is suitable; and

generating the proposed response upon a determination that the proposed response is suitable;

wherein parsing the language input comprises correlating each of the one or more classification keywords with at least one of a plurality of response models, and wherein the at least one response model comprises at least one of a plurality of language generation models.

2. The computer-implemented method of claim 1 , further comprising assigning a probability score to each of the one or more classification keywords indicating a likelihood that each of the one or more classification keywords is properly correlated to the at least one of the plurality of response models.

3. The computer-implemented method of claim 2 , further comprising selecting the response model based upon meeting or exceeding a threshold determination confirming the likelihood that each of the one or more classification keywords is properly correlated to the at least one of the plurality of response models.

4. The computer-implemented method of claim 1 , further comprising, determining whether a response can be generated based on the processing of the one or more classification keywords through the selected response model.

5. The computer-implemented method of claim 4 , further comprising selecting an alternative response model upon a determination that the response cannot be generated.

6. The computer-implemented method of claim 1 , further comprising determining whether the generated response is suitable for the received language input.

7. The computer-implemented method of claim 6 , further comprising selecting an alternative response model upon a determination that the generated response is not suitable for the received language input.

8. The computer-implemented method of claim 1 , wherein the response model comprises one of a language general model or an informational response model.

9. The computer-implemented method of claim 1 , further comprising translating the one or more keywords into a data query format upon selection of the at least one of the plurality of informational response models.

10. The computer-implemented method of claim 9 , further comprising querying a knowledge database and retrieving a factual response to the formatted data query.

11. The computer-implemented method of claim 10 , further comprising translating the factual response into a conversational response to be output as the generated response.

12. An apparatus, comprising:

a processor; and

a memory unit operatively connection to the processor, the memory unit including computer code configured to cause the processor:

receive a language input from a human user;

parse the language input to determine one or more keywords;

based on at least one of the one or more keywords, select at least one response model from a plurality of response models, wherein the at least one response model comprises at least one of a plurality of language generation models;

process the one or more keywords through the selected response model; and

generate a conversational response to received language input.

13. The apparatus of claim 12 , wherein the computer code further causes the processor to assign a probability value to each of the one or more keywords indicative of a likelihood that the respective keyword to which the probability value is assigned should be processed by one of the plurality of response models.

14. The apparatus of claim 12 , wherein the computer code further causes the processor to confirm selection of the at least one response model by comparing at least one of the probability values assigned to each of the one or more keywords to a threshold.

15. The apparatus of claim 12 , wherein the at least one response model comprises a response model adapted to generate a conversational response simulating a human response to the language input.

16. The apparatus of claim 12 , wherein the at least one response model comprises a response model adapted to return a knowledge-based response.

17. The apparatus of claim 16 , wherein the computer code further causes the processor to translate the knowledge-based response into a conversational response simulating a human response to the language input.

18. The apparatus of claim 12 , wherein the language input comprises at least one of an auditory input and a textual input.

Assignments (1)
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Dec 22, 2017
From: DOGGETT, ERIKA VARIS
To: DISNEY ENTERPRISES, INC.
Reel/Frame 044471/0558 →
Continuity (1)
Related Publication 20190197106A1 · Jun 27, 2019