IP Library Granted Patent US 10,134,060
Granted Patent B2
US 10,134,060 · App. 15/223,870 · Granted Nov 20, 2018

System and method for delivering targeted advertisements and/or providing natural language processing based on advertisements

Inventors: Tom Freeman (Mercer Island, WA); Mike Kennewick (Bellevue, WA)
Assignee: VB Assets, LLC
G06Q30/0269G06F17/275G06Q30/0241G06Q30/0242G06Q30/0251G10L15/18G10L15/26G10L15/265
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Quick Facts
Patent No.
US 10,134,060
App. No.
15/223,870
Granted
Nov 20, 2018
Kind
B2
Abstract

The system and method described herein may use various natural language models to deliver targeted advertisements and/or provide natural language processing based on advertisements. In one implementation, an advertisement associated with a product or service may be provided for presentation to a user. A natural language utterance of the user may be received. The natural language utterance may be interpreted based on the advertisement and, responsive to the existence of a pronoun in the natural language utterance, a determination of whether the pronoun refers to one or more of the product or service or a provider of the product or service may be effectuated.

Claims (70)

1. A method of processing natural language utterances that include requests, and selecting and presenting advertisements based thereon, the method being implemented by one or more physical processors programmed with computer program instructions which, when executed, cause the one or more physical processors to perform the method, the method comprising:

providing a natural language utterance as an input to a speech recognition engine;

receiving words or phrases, recognized from the natural language utterance, as an output of the speech recognition engine;

providing the words or phrases as an input to a conversational language processor;

receiving, from the conversational language processor, an interpretation of the natural language utterance based on the recognized words or phrases;

determining a context for the natural language utterance based at least on the recognized words or phrases;

determining that the natural language utterance includes a cross-application request based on the interpretation of the natural language utterance, the cross-application request comprising at least a first request and a second request to be serviced by different context-appropriate applications;

providing the first request to a first application to service the first request;

providing the second request to a second application to service the second request;

selecting an advertisement based at least on the determined context and either or both of the first request or the second request;

generating a service output responsive to the natural language utterance, the service output comprising:

(i) a first output received from the first application responsive to the first request;

(ii) a second output received from the second application responsive to the second request; and

(iii) the selected advertisement; and

providing the service output via an output device.

2. The method of claim 1 , further comprising:

mapping, by the speech recognition engine, a stream of phonemes contained in the natural language utterance to one or more syllables that are phonemically represented in an acoustic grammar to recognize the words or phrases;

wherein providing the words or phrases comprises generating a preliminary interpretation, by the speech recognition engine, for the natural language utterance from the one or more syllables; and

wherein the preliminary interpretation generated from the one or more syllables includes the recognized words or phrases.

3. The method of claim 1 , further comprising:

using an environmental model to determine environmental information, wherein determining a context for the natural language utterance is further based on the environmental information.

4. The method of claim 3 , wherein the environmental information comprises a user location, a user activity, or a user action.

5. The method of claim 1 , wherein determining that the natural language utterance includes a cross-application request is further based on the determined context.

6. A system for processing natural language utterances that include requests, and selecting and presenting advertisements based thereon, the system comprising:

one or more physical processors programmed with computer program instructions which, when executed, cause the one or more physical processors to:

provide a natural language utterance as an input to a speech recognition engine;

receive words or phrases, recognized from the natural language utterance, as an output of the speech recognition engine;

provide the words or phrases as an input to a conversational language processor;

receive, from the conversational language processor, an interpretation of the natural language utterance based on the recognized words or phrases;

determine a context for the natural language utterance based at least on the recognized words or phrases;

determine that the natural language utterance includes a cross-application request based on the interpretation of the natural language utterance, the cross-application request comprising at least a first request and a second request to be serviced by different context-appropriate applications;

provide the first request to a first application to service the first request;

provide the second request to a second application to service the second request;

select an advertisement based at least on the determined context and either or both of the first request or the second request;

generate a service output responsive to the natural language utterance, the service output comprising:

(i) a first output received from the first application responsive to the first request;

(ii) a second output received from the second application responsive to the second request; and

(iii) the selected advertisement; and

provide the service output via an output device.

7. The system of claim 6 , wherein the one or more physical processors are further programmed to:

map, via the speech recognition engine, a stream of phonemes contained in the natural language utterance to one or more syllables that are phonemically represented in an acoustic grammar to recognize the words or phrases;

wherein to provide the words or phrases, the one or more physical processors are programmed to generate a preliminary interpretation for the natural language utterance from the one or more syllables; and

wherein the preliminary interpretation generated from the one or more syllables includes the recognized words or phrases.

8. The system of claim 6 , wherein the one or more physical processors are further programmed to:

use an environmental model to determine environmental information, wherein the context for the natural language utterance is determined based further on the environmental information.

9. The system of claim 8 , wherein the environmental information comprises a user location, a user activity, or a user action.

10. The system of claim 6 , wherein the determined cross-application request is based further on the determined context.

11. A method of processing natural language utterances that include requests, and selecting and presenting purchase opportunities based thereon, the method being implemented by one or more physical processors programmed with computer program instructions which, when executed, cause the one or more physical processors to perform the method, the method comprising:

providing a natural language utterance, that includes a request, as an input to a speech recognition engine;

receiving words or phrases, recognized from the natural language utterance, as an output of the speech recognition engine;

providing the recognized words or phrases as an input to a conversational language processor;

receiving, from the conversational language processor, an interpretation of the natural language utterance based on the recognized words or phrases;

determining that the natural language utterance further includes incomplete or unrecognized words or phrases such that insufficient information is available to determine the request;

selecting a plurality of purchase opportunities, based at least in part on the interpreted natural language utterance, responsive to the determination that the natural language utterance further includes incomplete or unrecognized words or phrases such that insufficient information is available to determine the request;

presenting the plurality of purchase opportunities to a user via an output device;

receiving an indication that a user interaction has occurred with at least one of the plurality of purchase opportunities;

determining the request based on the interpretation of the natural language utterance and a context of the at least one purchase opportunity with which the user interaction occurred; and

servicing the request.

12. A system for processing natural language utterances that include requests, and selecting and presenting purchase opportunities based thereon, the system comprising:

one or more physical processors programmed with computer program instructions which, when executed, cause the one or more physical processors to:

provide a natural language utterance, that includes a request, as an input to a speech recognition engine;

receive words or phrases, recognized from the natural language utterance, as an output of the speech recognition engine;

provide the recognized words or phrases as an input to a conversational language processor;

receive, from the conversational language processor, an interpretation of the natural language utterance based on the recognized words or phrases;

determine that the natural language utterance further includes incomplete or unrecognized words or phrases such that insufficient information is available to determine the request;

select a plurality of purchase opportunities, based at least in part on the interpreted natural language utterance, responsive to the determination that the natural language utterance further includes incomplete or unrecognized words or phrases such that insufficient information is available to determine the request;

present the plurality of purchase opportunities to a user via an output device;

receive an indication that a user interaction has occurred with at least one of the plurality of purchase opportunities;

determine the request based on the interpretation of the natural language utterance and a context of the at least one purchase opportunity with which the user interaction occurred; and

service the request.

Assignments (10)
SECURITY INTEREST Recorded Apr 8, 2025
From: VB ASSETS, LLC
To: CONTINGENCY CAPITAL FUND A LP
Reel/Frame 070767/0583 →
CORRECTIVE ASSIGNMENT TO CORRECT THE ASSIGNOR'S NAME AND ASSIGNEE'S NAME PREVIOUSLY RECORDED AT REEL: 051581 FRAME: 0216. ASSIGNOR(S) HEREBY CONFIRMS THE ASSIGNMENT OF ASSIGNOR'S INTEREST.. Recorded Sep 22, 2020
From: VOICEBOX TECHNOLOGIES CORPORATION
To: VB ASSETS, LLC
Reel/Frame 053851/0873 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Jan 22, 2020
From: VB ASSETTS LLC
To: NUANCE COMMUNICATIONS, INC.
Reel/Frame 051581/0216 →
RELEASE OF SECURITY INTEREST Recorded Jun 13, 2019
From: DELPHI ASSET MANAGEMENT CORPORATION
To: VB ASSETS, LLC
Reel/Frame 049459/0596 →
SECURITY INTEREST Recorded Apr 12, 2019
From: VB ASSETS, LLC
To: DELPHI ASSET MANAGEMENT CORPORATION
Reel/Frame 048872/0831 →
NUNC PRO TUNC ASSIGNMENT Recorded Jul 25, 2018
From: VOICEBOX TECHNOLOGIES CORPORATION
To: VB ASSETS, LLC
Reel/Frame 046456/0128 →
RELEASE OF SECURITY INTEREST Recorded Apr 5, 2018
From: ORIX GROWTH CAPITAL, LLC
To: VOICEBOX TECHNOLOGIES CORPORATION
Reel/Frame 045581/0630 →
SECURITY INTEREST Recorded Dec 22, 2017
From: VOICEBOX TECHNOLOGIES CORPORATION
To: ORIX GROWTH CAPITAL, LLC
Reel/Frame 044949/0948 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Jul 29, 2016
From: FREEMAN, TOM; KENNEWICK, MIKE
To: VOICEBOX TECHNOLOGIES, INC.
Reel/Frame 039294/0062 →
MERGER Recorded Jul 29, 2016
From: VOICEBOX TECHNOLOGIES, INC.
To: VOICEBOX TECHNOLOGIES CORPORATION
Reel/Frame 039507/0654 →
Continuity (7)
Continuation 14836606 · Aug 26, 2015
Continuation 14537598 · Nov 10, 2014
Continuation 14016757 · Sep 3, 2013
Continuation 13371870 · Feb 13, 2012
Continuation 12847564 · Jul 30, 2010
Continuation 11671526 · Feb 6, 2007
Related Publication 20160335676A1 · Nov 17, 2016