System and method for speech to text translation using cores of a natural liquid architecture system

• US 10,621,988 B2
• Filed: 05/08/2017
• Issued: 04/14/2020
• Est. Priority Date: 10/26/2005
• Status: Active Grant

• Current Assignee: Cortica Ltd.
• Original Assignee: Cortica Ltd.
• Inventors: Raichelgauz, Igal, Odinaev, Karina, Zeevi, Yehoshua Y
• Primary Examiner(s): Woo, Isaac M
• Application Number:
  US15/589,558
• Publication Number:
  US 20170243583A1
• Time in Patent Office: 1,072 Days
• Field of Search: 707600-899
• CPC Class Codes: G06F 16/41 Indexing; Data structures therefor; Storage structures
• CPC Class Codes: G06F 16/685 using automatically derived transcript of audio data, e.g. lyrics speech recognition G10L15/00
• CPC Class Codes: G10L 15/005 Language recognition
• CPC Class Codes: G10L 15/20 Speech recognition techniques specially adapted for robustness in adverse environments, e.g. in noise, of stress induced speech G10L21/02 takes precedence
• CPC Class Codes: G10L 15/26 Speech to text systems G10L15/08 takes precedence

Abstract

A system and method for speech-to-text translation. The method includes determining, based on at least one audio input in a first language, at least one original language concept; identifying, based on the determined at least one original language concept, the first language of the at least one audio input; determining, for each original language concept, a matching translated concept, wherein each matching translated concept is associated with a second language, wherein the second language is different from the first language; generating a textual output based on the determined at least one translated concept.

Claims

1. A method for speech-to-text translation, comprising:

determining, based on at least one audio input in a first language, at least one original language concept;

identifying, based on the determined at least one original language concept, the first language of the at least one audio input;

determining, for each original language concept, a matching translated concept, wherein each matching translated concept is associated with a second language, wherein the second language is different from the first language; and

generating a textual output based on the determined at least one translated concept.

2. The method of claim 1, further comprising:

selecting the second language based on past interactions of a user with multimedia.

3. The method of claim 1, wherein each matching translated concept is statistically proximate to one of the at least one original language concept.

4. The method of claim 3, wherein each signature is robust to noise and distortion.

5. The method of claim 3, wherein each signature is generated by a signature generator system, wherein the signature generator system includes a plurality of at least partially statistically independent computational cores, wherein the properties of each core are set independently of the properties of each other core.

6. The method of claim 1, further comprising:

generating at least one signature for the at least one audio input, wherein the at least one original language concept is determined further based on the generated at least one signature.

7. The method of claim 6, wherein determining the at least one original language concept further comprises:

determining at least one previously generated signature that matches the generated at least one signature, wherein each matching signature represents one of the at least one original language concept.

8. The method of claim 7, wherein each concept is a collection of signatures and metadata representing the concept.

9. The method of claim 1, comprising selecting the second language based on a user profile.

10. The method according to claim 1 wherein each concept is a collection of signatures and is an abstract description of contents for which the signatures of the concept were generated.

11. The method according to claim 1 herein the at least one input audio comprises a speech segment;

wherein the method comprises generating at least one signature for the speech segment by breaking down the speech segment to multiple patches of random length and of random position in the speech segment.

12. A non-transitory computer readable medium having stored thereon instructions for causing a processing circuitry to execute a process, the process comprising:

determining, based on at least one audio input in a first language, at least one original language concept;

identifying, based on the determined at least one original language concept, the first language of the at least one audio input;

determining, for each original language concept, a matching translated concept, wherein each matching translated concept is associated with a second language, wherein the second language is different from the first language; and

generating a textual output based on the determined at least one translated concept.

20. The non-transitory computer readable medium according to claim 12 wherein each concept is a collection of signatures and is an abstract description of contents for which the signatures of the concept were generated.

21. The non-transitory computer readable medium according to claim 12 wherein the at least one input audio comprises a speech segment;

wherein the method comprises generating at least one signature for the speech segment by breaking down the speech segment to multiple patches of random length and of random position in the speech segment.

13. A system for speech-to-text translation, comprising:

a processing circuitry; and

a memory connected to the processing circuitry, the memory containing instructions that, when executed by the processing circuitry, configure the system to;

determine, based on at least one audio input in a first language;

at least one original language concept, identify, based on the determined at least one original language concept, the first language of the at least one audio input;

determine, for each original language concept, a matching translated concept, wherein each matching translated concept is associated with a second language, wherein the second language is different from the first language; and

generate a textual output based on the determined at least one translated concept.

14. The system of claim 13, wherein each matching translated concept is statistically proximate to one of the at least one original language concept.

15. The system of claim 14, wherein each signature is robust to noise and distortion.

16. The system of claim 14, further comprising:

a signature generator system, wherein each signature is generated by the signature generator system, wherein the signature generator system includes a plurality of at least partially statistically independent computational cores, wherein the properties of each core are set independently of the properties of each other core.

17. The system of claim 13, wherein the system is further configured to:

generate at least one signature for the at least one audio input, wherein the at least one original language concept is determined further based on the generated at least one signature.

18. The system of claim 17, wherein the system is further configured to:

determine at least one previously generated signature that matches the generated at least one signature, wherein each matching signature represents one of the at least one original language concept.

19. The system of claim 18, wherein each concept is a collection of signatures and metadata representing the concept.

22. The system of claim 13, wherein the system is further configured to select the second language based on past interactions of a user with multimedia.

23. The system of claim 13, wherein the system is further configured to select the second language based on a user profile.

24. The system according to claim 13 wherein each concept is a collection of signatures and is an abstract description of contents for which the signatures of the concept were generated.

25. The system according to claim 13 wherein the at least one input audio comprises a speech segment;

wherein the system comprises a signature generator system that is configured to generate at least one signature for the speech segment by breaking down the speech segment to multiple patches of random length and of random position in the speech segment.