Location-Based Conversational Understanding

• US 20160118046A1
• Filed: 01/07/2016
• Published: 04/28/2016
• Est. Priority Date: 03/31/2011
• Status: Active Grant

• Current Assignee: Microsoft Technology Licensing LLC (Microsoft Corporation)
• Original Assignee: Microsoft Technology Licensing LLC (Microsoft Corporation)
• Inventors: Heck, Larry Paul, Chinthakunta, Madhusudan, Mitby, David, Stifelman, Lisa
• Granted Patent: US 10,049,667 B2
• Time in Patent Office: Days
• US Class Current: 1/1
• CPC Class Codes: G06F 16/243 Natural language query formulation
• CPC Class Codes: G06F 16/24522 Translation of natural language queries to structured queries
• CPC Class Codes: G06F 16/24575 using context
• CPC Class Codes: G06F 16/29 Geographical information databases
• CPC Class Codes: G10L 15/20 Speech recognition techniques specially adapted for robustness in adverse environments, e.g. in noise, of stress induced speech G10L21/02 takes precedence
• CPC Class Codes: G10L 15/22 Procedures used during a speech recognition process, e.g. man-machine dialogue
• CPC Class Codes: G10L 15/26 Speech to text systems G10L15/08 takes precedence
• CPC Class Codes: G10L 2015/228 of application context

Abstract

Location-based conversational understanding may be provided. Upon receiving a query from a user, an environmental context associated with the query may be generated. The query may be interpreted according to the environmental context. The interpreted query may be executed and at least one result associated with the query may be provided to the user.

Claims

1. A method for providing location-based conversational understanding, the method comprising:

receiving a query from a user;

generating an environmental context associated with the query;

interpreting the query according to the environmental context;

executing the interpreted query; and

providing at least one result of the query to the user.

2. The method of claim 1, further comprising performing a speech-to-text conversion on the query.

3. The method of claim 1, wherein interpreting the query comprises adapting at least one conversational understanding model according to at least one previous query received from the location.

4. The method of claim 3, wherein the at least one conversational understanding model comprises an acoustic model associated with a location from which the query was received.

5. The method of claim 4, wherein interpreting the query further comprises adapting the query according to at least one background sound associated with the query according to the acoustic model.

6. The method of claim 5, wherein the background sound is measured within the query.

7. The method of claim 6, further comprising storing the background sound as the acoustic characteristic associated with the location.

8. The method of claim 1, further comprising aggregating the environmental contexts associated with a plurality of queries from a plurality of users.

9. The method of claim 8, further comprising storing the aggregated environmental contexts associated with the location.

10. The method of claim 9, further comprising:

receiving a second speech-based query from a second user; and

interpreting the second speech-based query according to the aggregated environmental contexts.

11. The method of claim 9, wherein interpreting the query comprises increasing a statistical weighting of at least one predicted semantic concept according to the aggregated environmental contexts associated received from the location.

12. A computer-readable medium which stores a set of instructions which when executed performs a method for providing location-based conversational understanding, the method executed by the set of instructions comprising:

receiving a speech-based query from a user at a location;

loading an environmental context associated with the location;

converting the speech-based query to text according to the environmental context;

executing the converted query according to the environmental context; and

providing at least one result associated with the executed query to the user.

13. The computer-readable medium of claim 12, wherein the environmental context comprises at least one of the following:

a time of at least one previous query, a date of at least one previous query, a subject of at least one previous query, a semantic model comprising an ontology, an understanding model, and an acoustic model of the location.

14. The computer-readable medium of claim 12, wherein converting the speech-based query to text according to the environmental context comprises adapting the query according to an acoustic interference associated with the location.

15. The computer-readable medium of claim 12, further comprising storing a plurality of environmental contexts associated with a plurality of locations aggregated according to a plurality of queries received from a plurality of users.

16. The computer-readable medium of claim 12, further comprising:

receiving a correction to the converted text from the user; and

updating the environmental context according to the correction.

17. The computer-readable medium of claim 16, wherein updating the environmental context comprises modifying a probability associated with at least one word of the correction for application to a future query.

18. The computer-readable medium of claim 12, wherein the location is defined by at least one of the following:

a global positioning system location of the user, an area code associated with the user, a ZIP code associated with the user, and a proximity of the user to a landmark.

19. The computer-readable medium of claim 12, further comprising:

receiving a second speech-based query from the user at a second location;

loading a second environmental context associated with the second location;

converting the second speech-based query to text according to the second environmental context;

executing the converted query according to the second environmental context; and

providing at least one second result associated with the executed query to the user.

20. A system for providing location-based conversational understanding, the system comprising:

a memory storage; and

a processing unit coupled to the memory storage, wherein the processing unit is operative to;

receive a speech-based query from a user at a location,

determine whether an environmental context associated with the location exists in the memory storage,

in response to determining that the environmental context does not exist;

identify at least one acoustic interference in the speech-based query;

identify at least one subject associated with the speech-based query; and

create a new environmental context associated with the location for storing in the memory storage, wherein the at least one acoustic interference is associated with an acoustic model and wherein the at least one identified subject is associated with a semantic model,

in response to determining that the environmental context does exist, load the environmental context,

convert the speech-based query to a text-based query according to the environmental context, wherein being operative to convert the speech-based query to a text-based query according to the environmental context comprises being operative to adapt the query according at least one acoustic interference associated with the environmental context,

execute the text-based query according to the environmental context, wherein being operative to execute the text-based query according to the environmental context comprises being operative to execute the query according to the semantic model associated with the environmental context, and

provide at least one result of the executed text-based query to the user.