Digital voice communication advertising

• US 10,657,539 B2
• Filed: 06/29/2007
• Issued: 05/19/2020
• Est. Priority Date: 06/29/2007
• Status: Active Grant

• Current Assignee: Microsoft Technology Licensing LLC (Microsoft Corporation)
• Original Assignee: Microsoft Technology Licensing LLC (Microsoft Corporation)
• Inventors: Forbes, Scott C, Gnuschke, Jerald J, Moore, Tim M, Yee, Dawson
• Primary Examiner(s): Coupe, Anita
• Assistant Examiner(s): Pouncil, Darnell A
• Application Number:
  US11/771,483
• Publication Number:
  US 20090006193A1
• Time in Patent Office: 4,708 Days
• Field of Search: 705 14
• CPC Class Codes: G06Q 20/102 Bill distribution or payments
• CPC Class Codes: G06Q 30/02 Marketing; Price estimation or determination; Fundraising
• CPC Class Codes: G06Q 30/0256 User search
• CPC Class Codes: G06Q 30/0269 based on user profile or attribute
• CPC Class Codes: G06Q 30/0275 Auctions
• CPC Class Codes: G06Q 30/0277 Online advertisement
• CPC Class Codes: G06Q 30/0283 Price estimation or determination
• CPC Class Codes: G06Q 40/04 Trading; Exchange, e.g. stocks, commodities, derivatives or currency exchange

Abstract

Techniques for providing third party incentivized communications sessions are described. In some embodiments, a Voice over IP (VoIP) conversation is sampled for audio information such as a word, phrase, utterance, or phoneme that may be associated with an advertisement in a database. The database may be searched for the audio information, or in some embodiments a text equivalent of the audio information, and the associated advertisement may be served to a participant in the VoIP communication session. In some implementations, data from or about the conversation may be compiled for analysis.

Claims

1. A computer-implemented method for processing audio data, the computer-implemented method comprising:

receiving, by a recognition module in a server, an audio conversation from a client device;

converting, by the recognition module, the audio conversation into text that is representative of the audio conversation;

sampling, by the recognition module, the text for a word;

buffering, by the recognition module, at least a portion of the text during the sampling;

searching, by a content module in the server, in a database for a piece of content that is associated with the word, the searching including a backward sampling, wherein the backward sampling comprises;

identifying the word in the portion of the text, the word occurring at a first frequency that is less than a second frequency associated with a plurality of other words in conversations; and

at least partly in response to identifying the word, looking for a relevant word in a segment of the portion of the text, wherein the segment of the portion precedes the word, and wherein detection of the relevant word in combination with the word triggers provisioning of the piece of content; and

sending, by the content module, the provisioned piece of content to the client device.

2. The computer-implemented method as described in claim 1, further comprising pre-selecting a third party source of the piece of content from among one or more users in a network environment.

3. The computer-implemented method as described in claim 1, further comprising assessing a third party a fee for sending the provisioned piece of content to the client device, wherein the fee is dependent on a factor associated with one or more of user location, time, relevancy factor, at least one other word, user profile, user selected level associated with the piece of content, non-audio communication triggering the audio conversation, user interaction with the piece of content, number of users, bandwidth, or client device type.

4. The computer-implemented method as described in claim 1, further comprising determining the piece of content to be sent based on at least one of user location, time, relevancy factor, at least one other word, user profile, selected level associated with the piece of content, non-audio communication triggering the audio conversation, or client device type.

5. The computer-implemented method as described in claim 1, further comprising presenting a user interface for enabling a user to manage at least one of a level of participation in the audio conversation, an amount of data to be retained in association with the audio conversation, a format for providing pieces of content, an identity of the user, or a sample rate for the audio conversation.

6. The computer-implemented method as described in claim 1, further comprising providing a user an incentive selected from one or more of a service, a communication hardware device, a coupon, a reimbursement, or a fungible credit.

7. The computer-implemented method as described in claim 1, wherein sending the provisioned piece of content comprises sending the provisioned piece of content in a non-intrusive medium selected from one or more of video display, real-time video display, instant messaging, email messaging, voice mail messaging, Internet link, subsequent telephone call, subsequent offer to place a communication, or physical messaging.

8. The computer-implemented method as described in claim 1, further comprising compiling non-identifiable audio event data including the word associated with the piece of content and lacking data that identifies a user.

9. The computer-implemented method as described in claim 8, further comprising presenting a user interface for managing compiled audio event data.

10. The computer-implemented method as described in claim 1, further comprising accepting an unsolicited offer from a third party to designate the piece of content for words included in the database being searched.

11. One or more computer-readable storage media comprising computer-executable instructions that, when executed, direct a computing system to:

receive a portion of audio content from a client device;

convert the portion of the audio content into a computer recognizable representation of the portion of the audio content;

buffer at least a portion of the computer recognizable representation of the portion of the audio content to generate a buffered portion of the computer recognizable representation of the portion of the audio content;

identify a word in the buffered portion, the word occurring at a first frequency that is less than a second frequency associated with a plurality of other words in conversations;

at least partly in response to identifying the word, identify a relevant word in a segment of the buffered portion that precedes the word;

at least partly in response to identifying the relevant word, search a database for at least one piece of content that is associated with the word, the search locating the at least one piece of content;

in response to the search locating the at least one piece of content, send the at least one piece of content to the client device; and

assess a third party a fee for sending the at least one piece of content.

12. The one or more computer-readable storage media as described in claim 11, the instructions further to direct the computing system to select the third party based on a bid entered by the third party in an online auction.

13. The one or more computer-readable storage media as described in claim 11, wherein the fee depends on a factor associated with one or more of client device location, time, relevancy factor, another utterance, user profile, selected level associated with the piece of content, non-audio communication triggering the audio content, user interaction with the piece of content, number of users, client device bandwidth, or client device type.

14. The one or more computer-readable storage media as described in claim 11, the instructions further to direct the computing system to compile non-identifiable audio event data comprising data that does not identify users associated with the audio content.

15. A system comprising:

one or more processors;

memory, communicatively coupled to the one or more processors, that stores;

a database including a record associating a pre-selected word with a piece of content, wherein the pre-selected word occurs at a first frequency that is less than a second frequency associated with a plurality of other words in conversations;

one or more modules that;

receive an audio session from a client device;

convert the audio session to a computer recognizable representation of the audio session;

identify, in a buffered portion of the computer recognizable representation of the audio session, a word that matches the pre-selected word;

upon identifying the word that matches the pre-selected word, identify another word that precedes the word in the buffered portion of the computer recognizable representation of the audio session; and

upon identifying the other word, send the piece of content to the client device based at least in part on one or more parameters.

16. The system as described in claim 15, wherein the one or more parameters are set by a user and individual parameters of the one or more parameters indicate at least one of a level of participation, a format in which to receive pieces of content, or whether or not information associated with the pieces of content is to be retained.

17. The system as described in claim 15, wherein the one or more modules calculate an assessed fee for sending the piece of content to the client device based at least in part on at least one of a location of a user, a time, a relevancy factor, an utterance, a profile of the user, a selected level associated with the piece of content, a non-audio communication triggering the audio session, user interaction with the piece of content, a number of users participating in the audio session, client device bandwidth, or client device type.

18. The system as described in claim 15, wherein the one or more modules send the piece of content to the client device based on at least one of user location, time, relevancy factor, user profile, selected level associated with the piece of content, non-audio communication triggering the audio conversation, or client device type.

19. The system as described in claim 15, wherein the one or more modules convert the audio session to the computer recognizable representation of the audio session based at least in part on performing at least one of speech recognition processing or speech-to-text processing on the audio session.