Accessing content using a source-specific content-adaptable dialogue

• US 8,595,016 B2
• Filed: 12/23/2011
• Issued: 11/26/2013
• Est. Priority Date: 12/23/2011
• Status: Expired due to Fees

• Current Assignee: Angle LLC
• Original Assignee: Angle LLC
• Inventors: Van Sciver, James D., Bader, Christopher, Aliotti, Michael Anthony, Bong, David Carl
• Primary Examiner(s): Abebe, Daniel D
• Application Number:
  US13/336,639
• Publication Number:
  US 20130166292A1
• Time in Patent Office: 704 Days
• Field of Search: 704/9, 704/275, 707/708
• US Class Current: 704/275
• CPC Class Codes: G10L 13/04 Details of speech synthesis systems, e.g. synthesiser structure or memory management
• CPC Class Codes: G10L 15/22 Procedures used during a speech recognition process, e.g. man-machine dialogue

Abstract

A system for accessing content maintains a set of content selections associated with a first user. The system receives first original content from a first content source associated with a first one of the content selections associated with the first user. The system applies, to the first original content, a first rule (such as a parsing rule) that is specific to the first one of the content selections, to produce first derived content. The system changes the state of at least one component of a human-machine dialogue system (such as a text-to-act engine, a dialogue manager, or an act-to-text engine) based on the first derived content. The system may apply a second rule (such as a dialogue rule) to the first derived content to produce rule output and change the state of the human-machine dialogue system based on the rule output.

Claims

1. A method performed by at least one computer processor executing computer program instructions stored on a non-transitory computer-readable medium, wherein the method comprises:

(A) identifying, from among a plurality of content selection data associated with a user, first content selection data associated with the user;

(B) identifying a first content source associated with the first content selection data;

(C) identifying a first selection-specific rule set associated with the first content selection data;

(D) receiving first original content from the first content source;

(E) applying the first selection-specific rule set to the first original content to produce first rule output; and

(F) changing a state of at least one first component of a human-machine dialogue system based on the first rule output.

2. The method of claim 1, wherein the at least one first component comprises a text-to-act engine.

3. The method of claim 1, wherein the at least one first component comprises a dialogue manager.

4. The method of claim 1, wherein the at least one first component comprises an act-to-text engine.

5. The method of claim 1, further comprising:

(E) identifying, from among the plurality of content selection data associated with the user, second content selection data associated with the user, wherein the second content selection data differs from the first content selection data;

(F) identifying a second content source associated with the second content selection data;

(G) identifying a second selection-specific rule set associated with the second content source, wherein the second selection-specific rule set differs from the first selection-specific rule set;

(H) receiving second original content from the second content source;

(I) applying the second selection-specific rule set to the second original content to produce second rule output; and

(J) changing a state of at least one second component of the human-machine dialogue system based on the second rule output.

6. The method of claim 5, wherein the at least one first component is the same as the at least one second component.

7. The method of claim 5, wherein the at least one first component differs from the at least one second component.

8. The method of claim 1, wherein the first selection-specific rule set comprises a first parsing rule.

9. The method of claim 1, wherein the first selection-specific rule set comprises a first dialogue rule.

10. The method of claim 1, wherein (A) comprises:

(A)(1) outputting a first audio stream representing content selection set data, wherein the content selection set data represents the plurality of content selection data associated with the user; and

(A)(2) receiving, from the user, first user input indicating the first content selection data associated with the user.

11. The method of claim 10, wherein (A) further comprises:

(A)(3) before (A)(1), providing, to a selection server that is functionally independent of the content source, a first request for the content selection set data; and

(A)(2) before (A)(1), receiving, from the selection server, the content selection set data.

12. The method of claim 11:

wherein the content selection set data includes the first content selection data; and

wherein the first content selection data includes the first selection-specific rule.

13. The method of claim 12:

wherein the content selection set data further includes second content selection data associated with the user, wherein the second content selection data is associated with a second content source that differs from the first content source; and

wherein the second content selection data includes a second selection-specific rule that differs from the first selection-specific rule.

14. The method of claim 10, wherein (B) comprises:

(B)(1) identifying the first content source associated with the first content selection data based on the first user input indicating the first content selection data.

15. The method of claim 10, wherein the first user input comprises voice input representing first speech of the user.

16. The method of claim 15:

wherein the human-machine dialogue system comprises a plurality of components including a speech-to-text engine, a text-to-act engine, a dialogue manager, an act-to-text engine, and a text-to-speech engine;

wherein the plurality of components includes the at least one first component; and

wherein the method further comprises;

(G) applying the speech-to-text engine to the voice input to produce first text;

(H) applying the text-to-act engine to the first text to produce first act data;

(I) applying the dialogue manager to the first act data to produce first response act data;

(J) applying the act-to-text engine to the first response act data to produce second text;

(K) applying the text-to-speech engine to the second text to produce speech data representing second speech; and

(L) producing audio output representing the speech data.

17. The method of claim 16, wherein the at least one first component comprises the text-to-act engine.

18. The method of claim 16, wherein the at least one component comprises the dialogue manager.

19. The method of claim 16, wherein the at least one component comprises the act-to-text engine.

20. The method of claim 16:

wherein (A)(2) comprises receiving the first user input from the user via an input component of a user device; and

wherein the user device includes the human-machine dialogue system.

21. The method of claim 1:

wherein the first selection-specific rule set comprises a first parsing rule associated with the first content selection; and

wherein (E) comprises;

(E)(1) applying the first parsing rule to the first original content to produce first derived content;

(E) (2) identifying a first dialogue rule associated with the first content selection; and

(E) (3) applying the first dialogue rule to the first derived content to produce the first rule output.

22. The method of claim 1, wherein (D) comprises:

(D)(1) identifying first authentication data associated with the user and the first content source;

(D)(2) authenticating the user at the first content source using the first authentication data; and

(D)(3) receiving the first original content from the first content source after authenticating the user at the first content source.

23. The method of claim 22, further comprising:

(G) identifying, from among the plurality of content selection data associated with the user, second content selection data associated with the user, wherein the second content selection data differs from the first content selection data;

(H) identifying a second content source associated with the second content selection data;

(I) identifying a second selection-specific rule set associated with the second content selection data; and

(J) receiving second original content from the second content source, comprising;

(J)(1) identifying second authentication data associated with the user and the second content source, wherein the second authentication data differs from the first authentication data;

(J)(2) authenticating the user at the second content source using the second authentication data; and

(J)(3) receiving the second original content from the second content source after authenticating the user at the second content source.

24. The method of claim 1, wherein the first selection-specific rule set consists of a single selection-specific rule.

25. The method of claim 24, wherein the first selection-specific rule set comprises a plurality of selection-specific rules.

26. A computer-readable medium comprising computer program instructions stored on a non-transitory computer-readable medium, wherein the instructions are executable by at least one computer processor to perform a method comprising:

(A) identifying, from among a plurality of content selection data associated with a user, first content selection data associated with the user;

(B) identifying a first content source associated with the first content selection data;

(C) identifying a first selection-specific rule set associated with the first content selection data;

(D) receiving first original content from the first content source;

(E) applying the first selection-specific rule set to the first original content to produce first rule output; and

(F) changing a state of at least one first component of a human-machine dialogue system based on the first rule output.

27. The computer-readable medium of claim 26, wherein the at least one first component comprises a text-to-act engine.

28. The computer-readable medium of claim 26, wherein the at least one first component comprises a dialogue manager.

29. The computer-readable medium of claim 26, wherein the at least one first component comprises an act-to-text engine.

30. The computer-readable medium of claim 26, wherein the method further comprises:

(E) identifying, from among the plurality of content selection data associated with the user, second content selection data associated with the user, wherein the second content selection data differs from the first content selection data;

(F) identifying a second content source associated with the second content selection data;

(G) identifying a second selection-specific rule set associated with the second content source, wherein the second selection-specific rule set differs from the first selection-specific rule set;

(H) receiving second original content from the second content source;

(I) applying the second selection-specific rule set to the second original content to produce second rule output; and

(J) changing a state of at least one second component of the human-machine dialogue system based on the second rule output.

31. The computer-readable medium of claim 30, wherein the at least one first component is the same as the at least one second component.

32. The computer-readable medium of claim 30, wherein the at least one first component differs from the at least one second component.

33. The computer-readable medium of claim 26, wherein the first selection-specific rule set comprises a first parsing rule.

34. The computer-readable medium of claim 26, wherein the first selection-specific rule set comprises a first dialogue rule.

35. The computer-readable medium of claim 26, wherein (A) comprises:

(A)(1) outputting a first audio stream representing content selection set data, wherein the content selection set data represents the plurality of content selection data associated with the user; and

(A)(2) receiving, from the user, first user input indicating the first content selection data associated with the user.

36. The computer-readable medium of claim 35, wherein (A) further comprises:

(A)(3) before (A)(1), providing, to a selection server that is functionally independent of the content source, a first request for the content selection set data; and

(A)(2) before (A)(1), receiving, from the selection server, the content selection set data.

37. The computer-readable medium of claim 36:

wherein the content selection set data includes the first content selection data; and

wherein the first content selection data includes the first selection-specific rule.

38. The computer-readable medium of claim 37:

wherein the content selection set data further includes second content selection data associated with the user, wherein the second content selection data is associated with a second content source that differs from the first content source; and

wherein the second content selection data includes a second selection-specific rule that differs from the first selection-specific rule.

39. The computer-readable medium of claim 35, wherein (B) comprises:

(B)(1) identifying the first content source associated with the first content selection data based on the first user input indicating the first content selection data.

40. The computer-readable medium of claim 35, wherein the first user input comprises voice input representing first speech of the user.

41. The computer-readable medium of claim 40:

wherein the human-machine dialogue system comprises a plurality of components including a speech-to-text engine, a text-to-act engine, a dialogue manager, an act-to-text engine, and a text-to-speech engine;

wherein the plurality of components includes the at least one first component; and

wherein the method further comprises;

(G) applying the speech-to-text engine to the voice input to produce first text;

(H) applying the text-to-act engine to the first text to produce first act data;

(I) applying the dialogue manager to the first act data to produce first response act data;

(J) applying the act-to-text engine to the first response act data to produce second text;

(K) applying the text-to-speech engine to the second text to produce speech data representing second speech; and

(L) producing audio output representing the speech data.

42. The computer-readable medium of claim 41, wherein the at least one first component comprises the text-to-act engine.

43. The computer-readable medium of claim 41, wherein the at least one component comprises the dialogue manager.

44. The computer-readable medium of claim 41, wherein the at least one component comprises the act-to-text engine.

45. The computer-readable medium of claim 41:

wherein (A)(2) comprises receiving the first user input from the user via an input component of a user device; and

wherein the user device includes the human-machine dialogue system.

46. The computer-readable medium of claim 26:

wherein the first selection-specific rule set comprises a first parsing rule associated with the first content selection; and

wherein (E) comprises;

(E)(1) applying the first parsing rule to the first original content to produce first derived content;

(E) (2) identifying a first dialogue rule associated with the first content selection; and

(E) (3) applying the first dialogue rule to the first derived content to produce the first rule output.

47. The computer-readable medium of claim 26, wherein (D) comprises:

(D)(1) identifying first authentication data associated with the user and the first content source;

(D)(2) authenticating the user at the first content source using the first authentication data; and

(D)(3) receiving the first original content from the first content source after authenticating the user at the first content source.

48. The computer-readable medium of claim 47, wherein the method further comprises:

(G) identifying, from among the plurality of content selection data associated with the user, second content selection data associated with the user, wherein the second content selection data differs from the first content selection data;

(H) identifying a second content source associated with the second content selection data;

(I) identifying a second selection-specific rule set associated with the second content selection data; and

(J) receiving second original content from the second content source, comprising;

(J)(1) identifying second authentication data associated with the user and the second content source, wherein the second authentication data differs from the first authentication data;

(J)(2) authenticating the user at the second content source using the second authentication data; and

(J)(3) receiving the second original content from the second content source after authenticating the user at the second content source.

49. The computer-readable medium of claim 26, wherein the first selection-specific rule set consists of a single selection-specific rule.

50. The computer-readable medium of claim 49, wherein the first selection-specific rule set comprises a plurality of selection-specific rules.