Synthesizing aggregate data of disparate data types into data of a uniform data type

• US 8,977,636 B2
• Filed: 08/19/2005
• Issued: 03/10/2015
• Est. Priority Date: 08/19/2005
• Status: Active Grant

• Current Assignee: International Business Machines Corporation
• Original Assignee: International Business Machines Corporation
• Inventors: Bodin, William K., Redman, Jerry W., Thorson, Derral C., Jaramillo, David
• Primary Examiner(s): MORRISON, JAY A
• Application Number:
  US11/207,911
• Publication Number:
  US 20070043758A1
• Time in Patent Office: 3,490 Days
• Field of Search: None
• US Class Current: 707/756
• CPC Class Codes: G06F 16/84 Mapping; Conversion
• CPC Class Codes: G06F 16/958 Organisation or management of web site content, e.g. publishing, maintaining pages or automatic linking

Abstract

Methods, systems, and products are disclosed for synthesizing the aggregated data of disparate data types into data of a uniform data type which includes receiving aggregated data of disparate data types and translating each of the aggregated data of disparate data types into text content and markup associated with the text content. Synthesizing the aggregated data of disparate data types into data of a uniform data type may also include dynamically creating grammar sets for the text content and associating the grammar sets with the text content. Associating the grammar sets with the text content includes inserting markup in the translated data.

Claims

1. A computer-implemented method for synthesizing aggregated data of disparate data types into data of a uniform data type comprising:

receiving aggregated data of disparate data types, wherein at least one of the aggregated data of disparate data types comprises non-text based audio or image data that cannot be accurately translated by a browser capable of rendering text and markup;

translating each of the aggregated data of disparate data types into translated data comprising text content and markup associated with the text content;

modifying content of the non-text based audio or image data to delete or augment at least some of the content;

dynamically creating grammar sets for the text content, further comprising;

identifying keywords determinative of the text content or logical structure of the translated data; and

creating grammars in dependence upon the keywords and grammar creation rules;

associating the grammar sets with the text content; and

associating actions respectively with each of the grammars, each of the actions being one of a plurality of predefined tasks for interacting with, modifying or managing the text content.

2. The method of claim 1 wherein associating the grammar sets with the text content further comprises inserting markup in the translated data.

3. The method of claim 1 wherein the identifying of keywords comprises comparing usage of potential keywords in the translated data with a predetermined usage threshold based on expected usage of the potential keywords.

4. The method of claim 1 further comprising:

receiving a user instruction communicating a predefined task among the plurality of predefined tasks;

recognizing the user instruction; and

performing said predefined task on the text content in response to recognizing the user instruction.

5. The method of claim 4 wherein the user instruction is a spoken user instruction;

and

wherein the recognizing of the spoken user instruction involves speech recognition of the spoken user instruction.

6. A system for synthesizing aggregated data of disparate data types into data of a uniform data type, the system comprising:

a computer processor;

a computer memory operatively coupled to the computer processor, the computer memory having disposed within it computer program instructions capable of;

receiving aggregated data of disparate data types, wherein at least one of the aggregated data of disparate data types comprises non-text based audio or image data that cannot be accurately translated by a browser capable of rendering text and markup;

translating each of the aggregated data of disparate data types into translated data comprising text content and markup associated with the text content;

modifying content of the non-text based audio or image data to delete or augment at least some of the content;

dynamically creating grammar sets for the text content, further comprising;

identifying keywords determinative of the text content or logical structure of the translated data; and

creating grammars in dependence upon the keywords and grammar creation rules;

associating the grammar sets with the text content; and

associating actions respectively with each of the grammars, each of the actions being one of a plurality of predefined tasks for interacting with, modifying or managing the text content.

7. The system of claim 6 wherein the computer memory also has disposed within it computer program instructions capable of inserting markup in the translated data.

8. The system of claim 6 wherein the identifying of keywords comprises comparing usage of potential keywords in the translated data with a predetermined usage threshold based on expected usage of the potential keywords.

9. The system of claim 6 wherein the computer program instructions further comprise:

receiving a user instruction communicating a predefined task among the plurality of predefined tasks;

recognizing the user instruction; and

performing said predefined task on the text content in response to recognizing the user instruction.

10. The system of claim 9 wherein the user instruction is a spoken user instruction;

and

wherein the recognizing of the spoken user instruction involves speech recognition of the spoken user instruction.

11. A computer program product for synthesizing aggregated data of disparate data types into data of a uniform data type, the computer program product embodied on a non-transistory computer-readable medium, the computer program product comprising:

computer program instructions for receiving aggregated data of disparate data types, wherein the aggregated data of disparate data types comprises non-text based audio or image data that cannot be accurately translated by a browser capable of rendering text and markup;

computer program instructions for translating each of the aggregated data of disparate data types into translated data comprising text content and markup associated with the text content;

modifying content of the non-text based audio or image data to delete or augment at least some of the content;

computer program instructions for dynamically creating grammar sets for the text content, further comprising;

computer program instructions for identifying keywords determinative of the text content or logical structure of the translated data; and

computer program instructions for creating grammars in dependence upon the keywords and grammar creation rules;

computer program instructions for associating the grammar sets with the text content; and

computer program instructions for associating actions respectively with each of the grammars, each of the actions being one of a plurality of predefined tasks for interacting with, modifying or managing the text content.

12. The computer program product of claim 11 wherein computer program instructions for associating the grammar sets with the text content further comprise computer program instructions for inserting markup in the translated data.

13. The computer program product of claim 11 wherein the identifying of keywords comprises comparing usage of potential keywords in the translated data with a predetermined usage threshold based on expected usage of the potential keywords.

14. The computer program product of claim 11 further comprising:

computer program instructions for receiving a user instruction communicating a predefined task among the plurality of predefined tasks;

computer program instructions for recognizing the user instruction; and

computer program instructions for performing said predefined task on the text content in response to recognizing the user instruction.

15. The computer program product of claim 14 wherein the user instruction is a spoken user instruction;

and

wherein the recognizing of the spoken user instruction involves speech recognition of the spoken user instruction.