System and method for generating advertisements for use in broadcast media

• US 20080109845A1
• Filed: 05/03/2007
• Published: 05/08/2008
• Est. Priority Date: 11/08/2006
• Status: Abandoned Application

• Current Assignee: MA Capital LLLP
• Original Assignee: MA Capital LLLP
• Inventors: DeMars, Robert, Hengel, Charles M.
• Application Number:
  US11/800,494
• Publication Number:
  US 20080109845A1
• Time in Patent Office: Days
• US Class Current: 725/36
• CPC Class Codes: G06Q 30/02 Marketing; Price estimation or determination; Fundraising
• CPC Class Codes: G10L 13/00 Speech synthesis; Text to speech systems

Abstract

This document describes, among other things, systems and methods for generating advertisements for use in broadcast media. A method comprises receiving an advertisement script at an online system; receiving a selection indicating a voice characteristic; and converting the advertisement script to an audio track using the selected voice characteristic.

Claims

1. A method for generating an audio advertisement, the method comprising:

receiving an advertisement script at an online system;

receiving a selection indicating a voice characteristic; and

converting the advertisement script to an audio track using the selected voice characteristic.

2. The method of claim 1, further comprising:

searching a database that comprises a plurality of voice samples for a voice sample that corresponds to the selected voice characteristic; and

using at least one of the plurality of voice samples to create the audio track.

3. The method of claim 2, wherein the plurality of voice samples include at least one of a recorded human voice or a synthesized voice.

4. The method of claim 1, wherein the voice characteristic is selected from the group of voice characteristics consisting of a gender of a speaker, a language of a speaker, an accent of a speaker, an age of a speaker, and an identity of a speaker.

5. The method of claim 1, further comprising:

analyzing the advertisement script; and

suggesting a revision to the advertisement script using the analysis.

6. The method of claim 5, wherein analyzing the advertisement script includes using a neural network.

7. The method of claim 5, wherein analyzing the advertisement script includes using discrete analysis.

8. The method of claim 5, wherein analyzing the advertisement script comprises:

deconstructing the advertisement script into a plurality of words;

determining an estimated efficacy of each word in the plurality of words; and

replacing a word when the estimated efficacy is below a threshold value.

9. The method of claim 8, wherein determining the estimated efficacy of each word comprises:

for each word, searching a database for a corresponding word; and

comparing the estimated efficacy of each word to an estimated efficacy of the corresponding word using a advertisement context based on an advertisement feature.

10. The method of claim 9, wherein the advertisement feature is selected from the group of advertisement features consisting of an advertisement type, a product, a sub-product, a advertisement length, a target market, and a target platform.

11. The method of claim 5, wherein analyzing the advertisement script comprises:

deconstructing the advertisement script into a plurality of phrases;

determining an estimated efficacy of each phrase in the plurality of phrases; and

replacing a phrase when the estimated efficacy is below a threshold value.

12. The method of claim 11, wherein determining the estimated efficacy of each phrase comprises:

for each phrase, searching a database for a corresponding phrase; and

comparing the estimated efficacy of each phrase to an estimated efficacy of the corresponding phrase, using a advertisement context based on an advertisement feature, wherein the advertisement feature is selected from the group of advertisement features consisting of an advertisement type, a product, a sub-product, a advertisement length, a target market, and a target platform.

13. The method of claim 1, further comprising:

analyzing the selected voice characteristic; and

suggesting a revision to the selected voice characteristic using the analysis.

14. The method of claim 13, wherein analyzing the selected voice characteristic includes using a neural network.

15. The method of claim 13, wherein analyzing the selected voice characteristic includes using discrete analysis.

16. A method comprising:

deconstructing an advertisement script into a plurality of words;

determining an estimated efficacy of each word in the plurality of words; and

replacing a word when the estimated efficacy is below a threshold value.

17. A system comprising:

a first module configured to receive an advertisement script at an online system;

a second module configured to receive a selection indicating a voice characteristic; and

a third module configured to convert the advertisement script to an audio track using the selected voice characteristic.

18. The system of claim 17, further comprising:

a fourth module configured to search a database that comprises a plurality of voice samples for a voice sample that corresponds to the selected voice characteristic; and

a fifth module configured to use at least one of the plurality of voice samples to create the audio track.

19. The system of claim 18, wherein the plurality of voice samples include at least one of a recorded human voice or a synthesized voice.

20. The system of claim 17, wherein the voice characteristic is selected from the group of voice characteristics consisting of a gender of a speaker, a language of a speaker, an accent of a speaker, an age of a speaker, and an identity of a speaker.

21. The system of claim 17, further comprising:

a sixth module configured to analyze the advertisement script; and

a seventh module configured to suggest a revision to the advertisement script using the analysis.

22. The system of claim 21, wherein the sixth module is further configured to:

deconstruct the advertisement script into a plurality of words;

determine an estimated efficacy of each word in the plurality of words; and

replace a word when the estimated efficacy is below a threshold value.

23. The system of claim 21, wherein the sixth module is further configured to:

deconstruct the advertisement script into a plurality of phrases;

determine an estimated efficacy of each phrase in the plurality of phrases; and

replace a phrase when the estimated efficacy is below a threshold value.

24. The system of claim 17, further comprising:

an eighth module configured to analyze the selected voice characteristic; and

a ninth module configured to suggest a revision to the selected voice characteristic using the analysis.

25. A computer-readable medium including instructions that, when performed by a computer, cause the computer to:

receive an advertisement script at an online system;

receive a selection indicating a voice characteristic; and

convert the advertisement script to an audio track using the selected voice characteristic.

26. The computer-readable medium of claim 25, further comprising instructions that cause the computer to:

search a database that comprises a plurality of voice samples for a voice sample that corresponds to the selected voice characteristic; and

use at least one of the plurality of voice samples to create the audio track.

27. The computer-readable medium of claim 26, wherein the plurality of voice samples include at least one of a recorded human voice or a synthesized voice.

28. The computer-readable medium of claim 25, wherein the voice characteristic is selected from the group of voice characteristics consisting of a gender of a speaker, a language of a speaker, an accent of a speaker, an age of a speaker, and an identity of a speaker.

29. The computer-readable medium of claim 25, further comprising instructions that cause the computer to:

analyze the advertisement script; and

suggest a revision to the advertisement script using the analysis.

30. The computer-readable medium of claim 29, wherein the instruction to analyze the advertisement script, further comprise instructions that cause the computer to:

deconstruct the advertisement script into a plurality of words;

determine an estimated efficacy of each word in the plurality of words; and

replace a word when the estimated efficacy is below a threshold value.

31. The computer-readable medium of claim 29, wherein the instruction to analyze the advertisement script, further comprise instructions that cause the computer to:

deconstruct the advertisement script into a plurality of phrases;

determine an estimated efficacy of each phrase in the plurality of phrases; and

replace a phrase when the estimated efficacy is below a threshold value.

32. The computer-readable medium of claim 25, further comprising instructions that cause the computer to:

analyze the selected voice characteristic; and

suggest a revision to the selected voice characteristic using the analysis.