System and method for delivering targeted advertisements and tracking advertisement interactions in voice recognition contexts

• US 8,527,274 B2
• Filed: 02/13/2012
• Issued: 09/03/2013
• Est. Priority Date: 02/06/2007
• Status: Active Grant

• Current Assignee: VB Assets, LLC
• Original Assignee: VoiceBox Technologies, Inc. (Microsoft Corporation)
• Inventors: Freeman, Tom, Kennewick, Mike
• Primary Examiner(s): ALBERTALLI, BRIAN LOUIS
• Application Number:
  US13/371,870
• Publication Number:
  US 20120150636A1
• Time in Patent Office: 568 Days
• Field of Search: None
• US Class Current: 704/257
• CPC Class Codes: G06F 40/263 Language identification
• CPC Class Codes: G06Q 30/0241 Advertisements
• CPC Class Codes: G06Q 30/0242 Determining effectiveness of advertisements
• CPC Class Codes: G06Q 30/0251 Targeted advertisements
• CPC Class Codes: G06Q 30/0269 based on user profile or attribute
• CPC Class Codes: G10L 15/18 using natural language modelling
• CPC Class Codes: G10L 15/26 Speech to text systems G10L15/08 takes precedence

Abstract

The system and method described herein may use various natural language models to deliver targeted advertisements and track advertisement interactions in voice recognition contexts. In particular, in response to an input device receiving an utterance, a conversational language processor may select and deliver one or more advertisements targeted to a user that spoke the utterance based on cognitive models associated with the user, various users having similar characteristics to the user, an environment in which the user spoke the utterance, or other criteria. Further, subsequent interaction with the targeted advertisements may be tracked to build and refine the cognitive models and thereby enhance the information used to deliver targeted advertisements in response to subsequent utterances.

Claims

1. A method to deliver targeted advertisements and track advertisement interactions in voice recognition contexts, comprising:

receiving a natural language utterance from a voice-enabled device;

processing the natural language utterance to identify one or more requests associated with the natural language utterance;

determining that the natural language utterance contains a request that is incomplete or ambiguous;

selecting one or more advertisements associated with the natural language utterance;

outputting the one or more selected advertisements to the voice-enabled device;

monitoring interaction between a user and the one or more selected advertisements; and

interpreting the request that is incomplete or ambiguous based on the interaction.

2. The method recited in claim 1, wherein the request that is incomplete or ambiguous includes one or more words that are unrecognized or incorrectly recognized.

3. The method recited in claim 1, further comprising:

generating a statistical profile based on the interaction between the user and the one or more selected advertisements.

4. The method recited in claim 3, wherein the statistical profile maps the one or more selected advertisements to demographic criteria, preference criteria, location criteria, presentation formats, conversion or click-through rates, or transaction or sale rates.

5. The method recited in claim 1, wherein the one or more selected advertisements include audible or hands-free messages if the voice-enabled device operates in a telematics environment.

6. The method recited in claim 1, further comprising:

generating a bill or invoice to one or more entities associated with the one or more selected advertisements.

7. The method recited in claim 6, wherein the bill or invoice includes a first cost if the interaction does not include a click-through, a second cost if the interaction includes the click-through, and a third cost if the interaction includes the click-through and a subsequent transaction or sale.

8. The method recited in claim 1, wherein processing the natural language utterance to identify one or more requests associated with the natural language utterance further comprises:

extracting one or more profile criteria from the natural language utterance.

9. The method recited in claim 8, wherein the one or more profile criteria include one or more words, phrases, concepts, semantic indicators, categories, topics, contexts, or requests associated with the natural language utterance.

10. The method recited in claim 8, wherein extracting the one or more profile criteria from the natural language utterance further comprises:

extracting the one or more profile criteria using a personalized cognitive model associated with a user that spoke the natural language utterance.

11. The method recited in claim 8, wherein extracting the one or more profile criteria from the natural language utterance further comprises:

extracting the one or more profile criteria using a generalized cognitive model associated with multiple different users.

12. The method recited in claim 8, wherein extracting the one or more profile criteria from the natural language utterance further comprises:

extracting the one or more profile criteria using an environmental model derived from conditions or surroundings associated with the voice-enabled device.

13. A system to deliver targeted advertisements and track advertisement interactions in voice recognition contexts, comprising:

one or more processors configured to;

receive a natural language utterance from a voice-enabled device;

process the natural language utterance to identify one or more requests associated with the natural language utterance;

determine that the natural language utterance contains a request that is incomplete or ambiguous;

select one or more advertisements associated with the natural language utterance;

output the one or more selected advertisements to the voice-enabled device;

monitor interaction between a user and the one or more selected advertisements; and

interpret the request that is incomplete or ambiguous based on the interaction.

14. The system recited in claim 13, wherein the request that is incomplete or ambiguous includes one or more words that are unrecognized or incorrectly recognized.

15. The system recited in claim 13, wherein the one or more processors are further configured to:

generate a statistical profile based on the interaction between the user and the one or more selected advertisements.

16. The system recited in claim 15, wherein the statistical profile maps the one or more selected advertisements to demographic criteria, preference criteria, location criteria, presentation formats, conversion or click-through rates, or transaction or sale rates.

17. The system recited in claim 13, wherein the one or more selected advertisements include audible or hands-free messages if the voice-enabled device operates in a telematics environment.

18. The system recited in claim 13, wherein the one or more processors are further configured to generate a bill or invoice to one or more entities associated with the one or more selected advertisements.

19. The system recited in claim 18, wherein the bill or invoice includes a first cost if the interaction does not include a click-through, a second cost if the interaction includes the click-through, and a third cost if the interaction includes the click-through and a subsequent transaction or sale.

20. The system recited in claim 13, wherein the one or more processors are further configured to:

extract one or more profile criteria from the natural language utterance.

21. The system recited in claim 20, wherein the one or more profile criteria include one or more words, phrases, concepts, semantic indicators, categories, topics, contexts, or requests associated with the natural language utterance.

22. The system recited in claim 20, wherein the one or more processors are further configured to:

extract the one or more profile criteria using a personalized cognitive model associated with a user that spoke the natural language utterance.

23. The system recited in claim 20, wherein the one or more processors are further configured to:

extract the one or more profile criteria using a generalized cognitive model associated with multiple different users.

24. The system recited in claim 20, wherein the one or more processors are further configured to:

extract the one or more profile criteria using an environmental model derived from conditions or surroundings associated with the voice-enabled device.