SPEECH RECOGNITION UTILIZING A DYNAMIC SET OF GRAMMAR ELEMENTS

• US 20140244259A1
• Filed: 12/29/2011
• Published: 08/28/2014
• Est. Priority Date: 12/29/2011
• Status: Abandoned Application

• Current Assignee: Tahoe Research Limited (f/k/a Learndale Limited) (Vector Capital Corporation)
• Original Assignee: Tahoe Research Limited (f/k/a Learndale Limited) (Vector Capital Corporation)
• Inventors: Rosario, Barbara, Lortz, Victor B., Rangarajan, Anand P., Kesavan, Vijay, Graumann, David L.
• Application Number:
  US13/977,522
• Publication Number:
  US 20140244259A1
• Time in Patent Office: Days
• US Class Current: 704/254
• CPC Class Codes: G10L 15/08 Speech classification or search
• CPC Class Codes: G10L 15/19 Grammatical context, e.g. disambiguation of the recognition hypotheses based on word sequence rules
• CPC Class Codes: G10L 2015/227 of the speaker; Human-factor methodology
• CPC Class Codes: G10L 2015/228 of application context

Abstract

Speech recognition is performed utilizing a dynamically maintained set of grammar elements. A plurality of grammar elements may be identified, and the grammar elements may be ordered based at least in part upon contextual information. In other words, contextual information may be utilized to bias speech recognition. Once a speech input is received, the ordered plurality of grammar elements may be evaluated, and a correspondence between the received speech input and a grammar element included in the plurality of grammar elements may be determined.

Claims

1. A speech recognition system comprising:

at least one memory configured to store a plurality of grammar elements;

at least one input device configured to receive a speech input; and

at least one processor configured to (i) identify at least one item of contextual information and (ii) determine, based at least in part upon the contextual information, a correspondence between the received speech input and a grammar element included in the plurality of grammar elements.

2. The speech recognition system of claim 1, wherein the at least one processor is further configured to identify a plurality of language models and direct, based at least in part upon the plurality of language models, storage of the plurality of grammar elements.

3. The speech recognition system of claim 1, wherein the contextual information comprises at least one of (i) an identification of a user, (ii) an identification of an action taken by an executing application, (iii) a parameter associated with a vehicle, (iv) a user gesture, or (v) a user input.

4. The speech recognition system of claim 1, wherein the at least one processor is further configured to order, based at least in part on the contextual information, the stored plurality of grammar elements and evaluate the ordered plurality of grammar elements to determine the correspondence between the received speech input and the grammar element.

5. A computer-implemented method comprising:

identifying, by a computing system comprising one or more computer processors, a plurality of grammar elements associated with speech recognition;

identifying, by the computing system, at least one item of contextual information;

ordering, by the computing system based at least in part on the contextual information, the plurality of grammar elements;

receiving, by the computing system, a speech input; and

determining, by the computing system based at least in part upon an evaluation of the ordered plurality of grammar elements, a correspondence between the received speech input and a grammar element included in the plurality of grammar elements.

6. The method of claim 5, wherein identifying a plurality of grammar elements comprises:

identifying a plurality of language models; and

determining, for each of the plurality of language models, a respective set of one or more grammar elements to be included in the plurality of grammar elements.

7. The method of claim 6, wherein identifying a plurality of language models comprises identifying at least one of (i) a language model associated with a user, (ii) a language model associated with an executing application, or (iii) a language model associated with a current location.

8. The method of claim 5, wherein identifying at least one item of contextual information comprises at least one of (i) identifying a user, (ii) identifying an action taken by an executing application, (iii) identifying a parameter associated with a vehicle, (iv) identifying a user gesture, or (v) identifying a user input.

9. The method of claim 5, wherein identifying a plurality of grammar elements comprises identifying a plurality of grammar elements associated with a plurality of executing applications.

10. The method of claim 9, wherein the plurality of applications comprise at least one of (i) a vehicle-based application or (ii) a network-based application.

11. The method of claim 5, wherein ordering the plurality of grammar elements comprises weighting the plurality of grammar elements based at least in part upon the contextual information.

12. The method of claim 5, further comprising:

translating, by the computing system, a recognized grammar element into an input; and

providing, by the computing system, the input to an application.

13. A system comprising:

at least one memory configured to store computer-executable instructions; and

at least one processor configured to access the at least one memory and execute the computer-executable instructions to;

identify a plurality of grammar elements associated with speech recognition;

receive a speech input;

identify at least one item of contextual information; and

determine, based at least in part upon the contextual information, a correspondence between the received speech input and a grammar element included in the plurality of grammar elements.

14. The system of claim 13, wherein the at least one processor is configured to identify the plurality of grammar elements by executing the computer-executable instructions to:

identify a plurality of language models; and

determine, for each of the plurality of language models, a respective set of one or more grammar elements to be included in the plurality of grammar elements.

15. The system of claim 14, wherein the plurality of language models comprise at least one of (i) a language model associated with a user, (ii) a language model associated with an executing application, or (iii) a language model associated with a current location.

16. The system of claim 13, wherein the contextual information comprises at least one of (i) an identification of a user, (ii) an identification of an action taken by an executing application, (iii) a parameter associated with a vehicle, (iv) a user gesture, or (v) a user input.

17. The system of claim 13, wherein the plurality of grammar elements comprise a plurality of grammar elements associated with a plurality of executing applications.

18. The system of claim 17, wherein the plurality of applications comprise at least one of (i) a vehicle-based application or (ii) a network-based application.

19. The system of claim 13, wherein the at least one processor is further configured to execute the computer-executable instructions to:

order, based at least in part on the contextual information, the plurality of grammar elements; and

evaluate the ordered plurality of grammar elements to determine the correspondence between the received speech input and the grammar element.

20. The system of claim 13, wherein the at least one processor is further configured to execute the computer-executable instructions to:

determine a probability between the received speech input and at least one grammar element included in the plurality of grammar elements; and

determine the correspondence based at least in part upon the determined probability.

21. The system of claim 13, wherein the at least one processor is further configured to execute the computer-executable instructions to:

translate a recognized grammar element into an input; and

direct provision of the input to an application.

22. At least one computer-readable medium comprising computer-executable instructions that, when executed by at least one processor, configure the at least one processor to:

identify a plurality of grammar elements associated with speech recognition;

receive a speech input;

identify at least one item of contextual information; and

determine, based at least in part upon the contextual information, a correspondence between the received speech input and a grammar element included in the plurality of grammar elements.

23. The computer-readable medium of claim 22, wherein the computer-executable instructions further configure the at least one processor to:

identify a plurality of language models; and

determine, for each of the plurality of language models, a respective set of one or more grammar elements to be included in the plurality of grammar elements.

24. The computer-readable medium of claim 23, wherein the plurality of language models comprise at least one of (i) a language model associated with a user, (ii) a language model associated with an executing application, or (iii) a language model associated with a current location.

25. The computer-readable medium of claim 22, wherein the contextual information comprises at least one of (i) an identification of a user, (ii) an identification of an action taken by an executing application, (iii) a parameter associated with a vehicle, (iv) a user gesture, or (v) a user input.

26. The computer-readable medium of claim 22, wherein the plurality of grammar elements comprise a plurality of grammar elements associated with a plurality of executing applications.

27. The computer-readable medium of claim 26, wherein the plurality of applications comprise at least one of (i) a vehicle-based application or (ii) a network-based application.

28. The computer-readable medium of claim 22, wherein the computer-executable instructions further configure the at least one processor to:

order, based at least in part on the contextual information, the plurality of grammar elements; and

evaluate the ordered plurality of grammar elements to determine the correspondence between the received speech input and the grammar element.

29. The computer-readable medium of claim 22, wherein the computer-executable instructions further configure the at least one processor to:

determine a probability between the received speech input and at least one grammar element included in the plurality of grammar elements; and

determine the correspondence based at least in part upon the determined probability.

30. The computer-readable medium of claim 22, wherein the computer-executable instructions further configure the at least one processor to:

translate a recognized grammar element into an input; and

direct provision of the input to an application.