SYSTEM AND METHOD FOR DYNAMICALLY GENERATING A RECOGNITION GRAMMAR IN AN INTEGRATED VOICE NAVIGATION SERVICES ENVIRONMENT

• US 20140156278A1
• Filed: 11/30/2012
• Published: 06/05/2014
• Est. Priority Date: 12/11/2007
• Status: Active Grant

• Current Assignee: Cerence Inc.
• Original Assignee: VoiceBox Technologies, Inc. (Microsoft Corporation)
• Inventors: Kennewick, Michael R., Cheung, Catherine, Baldwin, Larry, Salomon, Ari, Tjalve, Michael, Guttigoli, Sheetal, Armstrong, Lynn, Zimmerman, Bernie, Menaker, Sam, Di Christo, Philippe
• Granted Patent: US 8,983,839 B2
• Time in Patent Office: Days
• US Class Current: 704/254
• CPC Class Codes: G01C 21/3608 using speech input, e.g. using speech recognition
• CPC Class Codes: G06Q 30/0261 based on user location
• CPC Class Codes: G10L 15/00 Speech recognition G10L17/00 takes precedence
• CPC Class Codes: G10L 15/04 Segmentation; Word boundary detection
• 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 15/193 Formal grammars, e.g. finite state automata, context free grammars or word networks
• CPC Class Codes: G10L 15/22 Procedures used during a speech recognition process, e.g. man-machine dialogue

Abstract

The system and method described herein may dynamically generate a recognition grammar associated with a conversational voice user interface in an integrated voice navigation services environment. In particular, in response to receiving a natural language utterance that relates to a navigation context at the voice user interface, a conversational language processor may generate a dynamic recognition grammar that organizes grammar information based on one or more topological domains. For example, the one or more topological domains may be determined based on a current location associated with a navigation device, whereby a speech recognition engine may use the grammar information organized in the dynamic recognition grammar according to the one or more topological domains to generate one or more interpretations associated with the natural language utterance.

Claims

1-35. -35. (canceled)

36. A computer-implemented method of facilitating dynamic-recognition-grammar-based interpretation of one or more natural language utterance, the method being implemented by a computer system that includes one or more physical processors executing one or more computer program modules which, when executed, perform the method, the method comprising:

receiving a natural language utterance relating to a navigation context;

determining one or more similarities between a user associated with the natural language utterance and one or more other users;

determining a dynamic recognition grammar based on the one or more determined similarities; and

generating one or more interpretations associated with the natural language utterance based on the dynamic recognition grammar.

37. The method of claim 36, wherein the one or more determined similarities comprise a similar preference, a similar demographic profile, or a similar interest between the user and the one or more other users.

38. The method of claim 36, wherein the one or more determined similarities comprise a similar preference between the user and the one or more other users.

39. The method of claim 36, wherein the one or more determined similarities comprise a similar demographic profile between the user and the one or more other users.

40. The method of claim 36, wherein the one or more determined similarities comprise a similar interest between the user and the one or more other users.

41. The method of claim 36, wherein the one or more determined similarities comprise a similar preference and a similar demographic profile between the user and the one or more other users.

42. The method of claim 36, wherein the one or more determined similarities comprise a similar preference and a similar interest between the user and the one or more other users.

43. The method of claim 36, wherein the one or more determined similarities comprise a similar demographic profile and a similar interest between the user and the one or more other users.

44. The method of claim 36, wherein the one or more determined similarities comprise a similar preference, a similar demographic profile, and a similar interest between the user and the one or more other users.

45. The method of claim 36, wherein the dynamic recognition grammar comprises one or more dictionaries or phrases for interpreting the natural language utterance.

46. The method of claim 36, wherein the natural language utterance comprises one or more words from which a location is inferred, the method further comprising:

updating the dynamic recognition grammar based on information relating to the inferred location, a current location of the user, or a route from the current location to the location, wherein the information comprises traffic information, weather information, or event information relating to the inferred location, the current location, or the route; and

refining the one or more interpretations associated with the natural language utterance based on the updated dynamic recognition grammar.

47. The method of claim 46, the method further comprising:

determining the information relating to the inferred location, the current location, or the route based on preference information associated with the user.

48. The method of claim 36, wherein the natural language utterance comprises one or more words from which a location is inferred, the method further comprising:

determining information relating to the inferred location based on preference information associated with the user;

updating the dynamic recognition grammar based on information relating to the inferred location; and

refining the one or more interpretations associated with the natural language utterance based on the updated dynamic recognition grammar.

49. The method of claim 36, the method further comprising:

receiving a subsequent natural language utterance;

updating the dynamic recognition grammar based on the subsequent natural language utterance; and

refining the one or more interpretations associated with the natural language utterance based on the updated dynamic recognition grammar.

50. The method of claim 36, wherein the natural language utterance is received at an input device coupled to a navigation device, the method further comprising:

determining a current location associated with the navigation device, wherein the dynamic recognition grammar is further determined based on the current location.

51. The method of claim 50, the method further comprising:

downloading the dynamic recognition grammar to the navigation device from a remote source, wherein a size of the dynamic recognition grammar is constrained based on memory or resources available to the navigation device.

52. The method of claim 36, wherein the natural language utterance comprises one or more words from which a location is inferred, and wherein the dynamic recognition grammar is further determined based on information related to the inferred location, a current location relating to the user, or a route from the current location to the location, one or more topological domains associated with the current location, a subsequent natural language utterance, and/or an availability of memory or resources in the navigation device.

53. The method of claim 52, wherein the one or more topological domains are selected based on a geographic proximity between the current location and the one or more topological domains.

54. The method of claim 52, the method further comprising:

updating the dynamic recognition grammar in response to one or more changes to the one or more topological domains.

55. A system for facilitating dynamic-recognition-grammar-based interpretation of one or more natural language utterance, the system comprising one or more physical processors executing one or more computer program modules which, when executed, cause the system to:

receive a natural language utterance relating to a navigation context;

determine one or more similarities between a user associated with the natural language utterance and one or more other users;

determine a dynamic recognition grammar based on the one or more determined similarities; and

generate one or more interpretations associated with the natural language utterance based on the dynamic recognition grammar.