Dialog repair based on discrepancies between user model predictions and speech recognition results
First Claim
1. A system for repairing dialog data, comprising:
- a discrepancy detection component that identifies discrepancy data between predictive dialog data output from a user model prediction component and recognized dialog data output from a speech recognition component; and
a dialog repair component that repairs the dialog data based in part on the discrepancy data.
2 Assignments
0 Petitions
Accused Products
Abstract
An architecture is presented that leverages discrepancies between user model predictions and speech recognition results by identifying discrepancies between the predictive data and the speech recognition data and repairing the data based in part on the discrepancy. User model predictions predict what goal or action speech application users are likely to pursue based in part on past user behavior. Speech recognition results indicate what goal speech application users are likely to have spoken based in part on words spoken under specific constraints. Discrepancies between the predictive data and the speech recognition data are identified and a dialog repair is engaged for repairing these discrepancies. By engaging in repairs when there is a discrepancy between the predictive results and the speech recognition results, and utilizing feedback obtained via interaction with a user, the architecture can learn about the reliability of both user model predictions and speech recognition results for future processing.
204 Citations
20 Claims
-
1. A system for repairing dialog data, comprising:
-
a discrepancy detection component that identifies discrepancy data between predictive dialog data output from a user model prediction component and recognized dialog data output from a speech recognition component; and
a dialog repair component that repairs the dialog data based in part on the discrepancy data. - View Dependent Claims (2, 3, 4, 5, 6, 7)
-
-
8. A computer-implemented method for leveraging discrepancies between user model predictions and speech recognition results for repairing dialog data, comprising:
-
processing speech data into predicted dialog data and recognized dialog data;
comparing the predictive dialog data and the recognized dialog data to generate difference data;
processing the difference data to determine a degree of difference between the predictive dialog data and the recognized dialog data; and
changing at least one of the predicted dialog data, the recognized dialog data, and a potential action based in part on optimization of a specific system action. - View Dependent Claims (9, 10, 11, 12, 13, 14, 15, 16, 17, 18)
-
-
19. A computer-implemented system for repairing dialog data in a speech application, comprising:
-
computer-implemented means for identifying discrepancy data between predictive dialog data output from a predictive user model component and recognized dialog data output from a speech recognition component, the user model component and the speech recognition component each including a plurality of modifiable parameters and structures;
computer-implemented means for initiating a dialog repair process based in part on the discrepancy data; and
computer-implemented means for learning reliability of at least one of the user model prediction component and the speech recognition component based on user interaction data received as an expected consequence of taking a system action. - View Dependent Claims (20)
-
Specification