IP Library › Granted Patent US 10,217,457
Granted Patent B2
US 10,217,457 · App. 15/483,213 · Granted Feb 26, 2019

Learning from interactions for a spoken dialog system

Inventors: Mazin Gilbert (Warren, NJ); Esther Levin (Livingston, NJ); Michael Lederman Littman (Bernardsville, NJ); Robert E. Schapire (Princeton, NJ)
Assignees: AT&T INTELLECTUAL PROPERTY II, L.P.; RUTGERS, THE STATE UNIVERSITY OF NEW JERSEY
G10L15/065G06F17/2785G10L15/063G10L15/1815G10L15/26
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Quick Facts
Patent No.
US 10,217,457
App. No.
15/483,213
Granted
Feb 26, 2019
Kind
B2
Abstract

In one embodiment, a semantic classifier input and a corresponding label attributed to the semantic classifier input may be obtained. A determination may be made whether the corresponding label is correct based on logged interaction data. An entry of an adaptation corpus may be generated based on a result of the determination. Operation of the semantic classifier may be adapted based on the adaptation corpus.

Claims (44)

1. A method comprising:

obtaining a semantic classifier input for a semantic classifier and a corresponding label attributed to the semantic classifier input;

determining, via a processor, whether the corresponding label is correct based on logged interaction data, to yield a correctness result, wherein the logged interaction data comprises an input/output pair having an input and an output, the input comprising a speech recognition result in a lattice form and the output comprising one of an outcome of a call, a confirmation by a user, and a call hang-up; and

adapting operation of a spoken dialog system utilizing the semantic classifier based on the correctness result.

2. The method of claim 1 , wherein the output as a result of the input.

3. The method of claim 1 , wherein the logged interaction data further comprises:

data describing user speech; and

a non-speech user action indicating one of a negative training example and a positive training example.

4. The method of claim 1 , further comprising:

generating an entry for an adaptation corpus based on the correctness result.

5. The method of claim 4 , wherein adapting operation of the semantic classifier based on the correctness result further comprises adapting operation of the semantic classifier based on the adaptation corpus.

6. The method of claim 1 , wherein determining whether the corresponding label is correct indicates whether the corresponding label attributed by the semantic classifier is one of a correct label and an incorrect label.

7. The method of claim 1 , wherein determining whether the corresponding label is correct further comprises:

calculating a confidence level indicative of an estimated probability that the corresponding label attributed by the semantic classifier is correct to yield a calculated confidence level; and

determining that the corresponding label attributed by the semantic classifier is correct when the calculated confidence level is greater than a predetermined threshold.

8. A system comprising:

a processor; and

a computer-readable storage medium having instructions stored which, when executed by the processor, cause the processor to perform operations comprising:

obtaining a semantic classifier input for a semantic classifier and a corresponding label attributed to the semantic classifier input;

determining whether the corresponding label is correct based on logged interaction data, to yield a correctness result, wherein the logged interaction data comprises an input/output pair having an input and an output, the input comprising a speech recognition result in a lattice form and the output comprising one of an outcome of a call, a confirmation by a user, and a call hang-up; and

adapting operation of a spoken dialog system utilizing the semantic classifier based on the correctness result.

9. The system of claim 8 , wherein the output as a result of the input.

10. The system of claim 8 , wherein the logged interaction data further comprises:

data describing user speech; and

a non-speech user action indicating one of a negative training example and a positive training example.

11. The system of claim 8 , wherein the computer-readable storage medium stores additional instructions stored which, when executed by the processor, cause the processor to perform operations further comprising:

generating an entry for an adaptation corpus based on the correctness result.

12. The system of claim 11 , wherein adapting operation of the semantic classifier based on the correctness result further comprises adapting operation of the semantic classifier based on the adaptation corpus.

13. The system of claim 8 , wherein determining whether the corresponding label is correct indicates whether the corresponding label attributed by the semantic classifier is one of a correct label and an incorrect label.

14. The system of claim 8 , wherein determining whether the corresponding label is correct further comprises:

calculating a confidence level indicative of an estimated probability that the corresponding label attributed by the semantic classifier is correct to yield a calculated confidence level; and

determining that the corresponding label attributed by the semantic classifier is correct when the calculated confidence level is greater than a predetermined threshold.

15. A computer-readable storage device having instructions stored which, when executed by a processor, cause the processor to perform operations comprising:

obtaining a semantic classifier input for a semantic classifier and a corresponding label attributed to the semantic classifier input;

determining whether the corresponding label is correct based on logged interaction data, to yield a correctness result, wherein the logged interaction data comprises an input/output pair having an input and an output, the input comprising a speech recognition result in a lattice form and the output comprising one of an outcome of a call, a confirmation by a user, and a call hang-up; and

adapting operation of a spoken dialog system utilizing the semantic classifier based on the correctness result.

16. The computer-readable storage device of claim 15 , wherein the output as a result of the input.

17. The computer-readable storage device of claim 15 , wherein the logged interaction data further comprises:

data describing user speech; and

a non-speech user action indicating one of a negative training example and a positive training example.

18. The computer-readable storage device of claim 15 , wherein the computer-readable storage device stores additional instructions which, when executed by the processor, cause the processor to perform operations further comprising:

generating an entry for an adaptation corpus based on the correctness result.

19. The computer-readable storage device of claim 18 , wherein adapting operation of the semantic classifier based on the correctness result further comprises adapting operation of the semantic classifier based on the adaptation corpus.

20. The computer-readable storage device of claim 15 , wherein determining whether the corresponding label is correct indicates whether the corresponding label attributed by the semantic classifier is one of a correct label and an incorrect label.

Assignments (3)
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Apr 3, 2018
From: SCHAPIRE, ROBERT E.
To: AT&T CORP.
Reel/Frame 045427/0615 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Apr 3, 2018
From: LITTMAN, MICHAEL L.
To: RUTGERS, THE STATE UNIVERSITY OF NEW JERSEY
Reel/Frame 045427/0817 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Apr 3, 2018
From: GILBERT, MAZIN; LEVIN, ESTHER
To: AT&T CORP.
Reel/Frame 045830/0913 →
Continuity (2)
Continuation 11426748 · Jun 27, 2006
Related Publication 20170213546A1 · Jul 27, 2017