SYSTEM AND METHOD FOR EFFICIENT LASER PROCESSING OF A MOVING WEB-BASED MATERIAL

• US 20110015927A1
• Filed: 09/17/2010
• Published: 01/20/2011
• Est. Priority Date: 01/20/2004
• Status: Active Grant

• Current Assignee: Microsoft Technology Licensing LLC (Microsoft Corporation)
• Original Assignee: Microsoft Corporation
• Inventors: Hwang, Mei-Yuh, Mau, Peter, Yu, Dong, Acero, Alejandro
• Granted Patent: US 8,280,733 B2
• Time in Patent Office: Days
• US Class Current: 704/235
• CPC Class Codes: G10L 15/063 Training
• CPC Class Codes: G10L 15/065 Adaptation
• CPC Class Codes: G10L 2015/0631 Creating reference templates; Clustering

Abstract

An automatic speech recognition system recognizes user changes to dictated text and infers whether such changes result from the user changing his/her mind, or whether such changes are a result of a recognition error. If a recognition error is detected, the system uses the type of user correction to modify itself to reduce the chance that such recognition error will occur again. Accordingly, the system and methods provide for significant speech recognition learning with little or no additional user interaction.

Claims

1. 1. A computer-implemented speech recognition system, comprising:

a microphone that receives user speech;

a speech recognition engine coupled to the microphone, the speech recognition engine recognizing the user speech and providing a corresponding textual output on a user interface;

a change recognition component that automatically assigns a categorization to a user-initiated change to the corresponding textual output, wherein automatically assigning the categorization comprises automatically assigning based at least in part upon a measurement of time indicative of how long it took the user to initiate the change;

an adaptation component that selectively adapting the speech recognition engine depending upon the categorization.

2. The system of claim 1, wherein automatically assigning the categorization comprises automatically identifying, based at least in part upon the measurement of time, the user-initiated change as being either a correction or an edit operation.

3. The system of claim 1, wherein selectively adapting comprises adapting or not adapting depending upon the categorization.

4. The system of claim 1, wherein selectively adapting comprises adapting or not adapting depending upon whether the categorization is indicates that the user-initiated change is a correction or an edit operation.

5. The system of claim 1, wherein selectively adapting comprises not adapting if the categorization indicates that the user-initiated correction is not due to a recognition error made by the speech recognition engine.

6. The system of claim 1, wherein selectively adapting comprises adapting only if the categorization indicates that the user-initiated correction is due to a recognition error made by the speech recognition engine, and wherein adapting comprises adapting so as to make it less likely that the speech recognition engine will subsequently repeat the recognition error during a subsequent recognition operation.

7. The system of claim 1, wherein automatically assigning the categorization further comprises automatically assigning based at least in part on a measurement of a number of words changed as a result of the user-initiated change.

8. A computer-implemented for adapting a speech recognition system, comprising:

detecting a user-initiated change to dictated text;

automatically assigning a categorization to the user-initiated change to the dictated text, wherein automatically assigning the categorization comprises automatically assigning based at least in part upon a measurement of time indicative of how long it took the user to initiate the change; and

selectively adapting the speech recognition engine depending upon the categorization.

9. The method of claim 8, wherein automatically assigning the categorization comprises automatically identifying, based at least in part upon the measurement of time, the user-initiated change as being either a correction or an edit operation.

10. The method of claim 8, wherein selectively adapting comprises adapting or not adapting depending upon the categorization.

11. The method of claim 8, wherein selectively adapting comprises adapting or not adapting depending upon whether the categorization is indicates that the user-initiated change is a correction or an edit operation.

12. The method of claim 8, wherein selectively adapting comprises not adapting if the categorization indicates that the user-initiated correction is not due to a recognition error made by the speech recognition engine.

13. The method of claim 8, wherein selectively adapting comprises adapting only if the categorization indicates that the user-initiated correction is due to a recognition error made by the speech recognition engine, and wherein adapting comprises adapting so as to make it less likely that the speech recognition engine will subsequently repeat the recognition error during a subsequent recognition operation.

14. A computer-implemented for adapting a speech recognition system, comprising:

detecting a user-initiated change to dictated text;

automatically assigning a categorization to the user-initiated change to the dictated text, wherein automatically assigning the categorization comprises automatically assigning based at least in part upon a measurement of a number of words changed as a result of the user-initiated change; and

selectively adapting the speech recognition engine depending upon the categorization.

15. The method of claim 14, wherein automatically assigning the categorization comprises automatically identifying, based at least in part upon the measurement of the number of words, the user-initiated change as being either a correction or an edit operation.

16. The method of claim 14, wherein selectively adapting comprises adapting or not adapting depending upon the categorization.

17. The method of claim 14, wherein selectively adapting comprises adapting or not adapting depending upon whether the categorization is indicates that the user-initiated change is a correction or an edit operation.

18. The method of claim 14, wherein selectively adapting comprises not adapting if the categorization indicates that the user-initiated correction is not due to a recognition error made by the speech recognition engine.

19. The method of claim 14, wherein selectively adapting comprises adapting only if the categorization indicates that the user-initiated correction is due to a recognition error made by the speech recognition engine, and wherein adapting comprises adapting so as to make it less likely that the speech recognition engine will subsequently repeat the recognition error during a subsequent recognition operation.

20. The method of claim 14, wherein automatically assigning comprises automatically assigning based at least in part on a comparison of a speech recognition score of the dictated text to a speech recognition score of the dictated text after application of the user-initiated change.