METHOD AND SYSTEM FOR PROCESSING CONTENT

• US 20130332170A1
• Filed: 12/29/2011
• Published: 12/12/2013
• Est. Priority Date: 12/30/2010
• Status: Abandoned Application

• Current Assignee: Gal Melamed
• Original Assignee: Gal Melamed
• Inventors: Melamed, Gal
• Application Number:
  US13/977,268
• Publication Number:
  US 20130332170A1
• Time in Patent Office: Days
• US Class Current: 704/260
• CPC Class Codes: G10L 13/02 Methods for producing synthetic speech; Speech synthesisers
• CPC Class Codes: G10L 13/027 Concept to speech synthesisers; Generation of natural phrases from machine-based concepts generation of parameters for speech synthesis out of text G10L13/08
• CPC Class Codes: G10L 13/047 Architecture of speech synthesisers
• CPC Class Codes: G10L 13/08 Text analysis or generation of parameters for speech synthesis out of text, e.g. grapheme to phoneme translation, prosody generation or stress or intonation determination
• CPC Class Codes: G10L 13/086 Detection of language

Abstract

Provided are a method and system for processing user input and web based content by transforming content to metadata and by using a plurality of vocabularies, including specific vocabularies (e.g. location dependent, culture dependent, personalized, non formal, and more), and other methods to process voice or non-voice content.

Claims

1. A method for processing content, carried out using an electronic processor the method comprising

transforming non-voice content to metadata;

mapping the non voice content to the metadata;

transmitting the metadata to a connected device said connected device is configured to determine a single metadata object to use as input to a text-to-speech system;

converting the metadata to a format suitable for submitting to the text-to-speech system;

submitting the converted metadata to the text-to-speech system; and

presenting the non-voice content as speech.

2. The method according to claim 1 comprising extracting the non-voice content from a network.

4. The method according to claim 2 wherein the network comprises a social network, an instant messaging textual representation service or a combination thereof.

5. The method according to claim 1 wherein the non-voice content comprises informal text.

6. The method according to claim 5 comprising

extracting non-voice content from a web resource;

identifying informal text within the non-voice content; and

transforming the identified informal text to metadata prior to converting the metadata into a format suitable for submitting to a text-to-speech system.

7. The method according to claim 6 wherein transforming the identified informal text to metadata comprises

tagging the informal text in a platform specific manner to obtain tagged data;

and

transforming the tagged data to metadata.

8. The method according to claim 7 further comprising

detecting the language of the tagged data;

detecting misspelled content;

correcting spelling mistakes in the misspelled content;

detecting informal text content; and

transforming the informal text content to a format suitable for submitting to a text-to-speech system.

9. The method according to claim 8 comprising detecting misspelled content by using a dictionary of the detected language, wherein misspelled content is case insensitive.

10. The method according to claim 8 wherein detecting misspelled content comprises using metadata, the metadata comprising web related content and wherein the misspelled content is transformed to a format usable by a text-to-speech system.

11. The method according to claim 8 wherein the misspelled content comprises successive words with no blank spaces in between the words with or without special characters in between the words.

12. The method according to claim 8 wherein detecting informal text content comprises using metadata, the metadata comprising location and culture based information.

13. The method according to claim 8 comprising

detecting unidentified content other than the misspelled content and/or the informal text content;

and

inserting the unidentified content into an exception database.

20. The method according to claim 1 further comprising

extracting visual content from available resources;

and

generating a visual presentation of the visual content.

21. The method according to claim 20 wherein the visual presentation comprises voice content the origin of which is different than the origin of the visual content.

22. The method according to claim 20 wherein the available resources comprise public locations.

23. The method according to claim 20 wherein the visual presentation comprises a video.

29. The method according to claim 1 comprising:

choosing the metadata objects based on the connected device metadata, wherein

the choosing is preformed with reference to specific characteristics.

3. (canceled)

14-19. -19. (canceled)

24. A method for processing and presenting content to a user, the method being carried out on an electronic processor, the method comprising

receiving voice input from a web or connected device;

transforming pre-defined characteristics to metadata said metadata is configured to be used as input for a text-to-speech engine;

creating a specific vocabulary based on the metadata;

processing the voice input using a voice-to-text engine with at least one specific vocabulary and another vocabulary; and

generating from the processed voice input a command or text.

25. The method according to claim 24 wherein the at least one specific vocabulary is a platform specific vocabulary, a location based specific vocabulary or a user specific vocabulary.

26. The method according to claim 24 wherein creating a specific vocabulary is off line or on the fly.

27. The method according to claim 24 comprising processing a generic vocabulary together with a specific vocabulary.

28. The method according to claim 24 wherein the pre-defined characteristic consists of:

user personal information per the user account, such as age, gender, interest tags, hobbies, friends/contact list, groups, social activity history, Likes on specific content, check-in history, used vocabulary, user current physical geo-location, user'"'"'s geo-location history, social network, or common public topics and trends.

30. The method according to claim 24 wherein the at least one specific vocabulary is a platform specific vocabulary, or a location based specific vocabulary or a user specific vocabulary or a combination thereof.

31. The method according to claim 24, comprising creating the specific vocabulary from a group consisting of:

previous correspondence, and/or lists, and/or groups, and/or interests, and/or user current physical geo-location, and/or nearby venues, and/or music history, and/or check-in history, and/or friends names, and/or friends content.

32. The method according to claim 24, wherein the specific vocabulary comprises a specific vocabulary entry, said specific vocabulary entry is created

from a textual phrase that is transformed into metadata and wherein said metadata is configured to be inputted to text-to-speech engine.

33. The method according to claim 24, comprising:

including the metadata as part of the specific vocabulary, said specific vocabulary is configured to be inputted to voice-to-text engine.

34. The method according to claim 24, wherein the text is processed by invert transformation from said metadata to a textual phrase.