Selective machine translation with crowdsourcing

• US 9,659,009 B2
• Filed: 09/24/2014
• Issued: 05/23/2017
• Est. Priority Date: 09/24/2014
• Status: Active Grant

• Current Assignee: International Business Machines Corporation
• Original Assignee: International Business Machines Corporation
• Inventors: Wu, Cheng, Ni, Jian, Wan, Hui, Caskey, Sasha P., Sakrajda, Andrzej
• Primary Examiner(s): SPOONER, LAMONT M
• Application Number:
  US14/495,401
• Publication Number:
  US 20160085746A1
• Time in Patent Office: 972 Days
• Field of Search: 704 2- 8
• CPC Class Codes: G06F 40/49 using very large corpora, e.g. the web
• CPC Class Codes: G06F 40/58 Use of machine translation, e.g. for multi-lingual retrieval, for server-side translation for client devices or for real-time translation

Abstract

A structure and method for crowdsourcing includes evaluating a metric related to a content to be translated, determining a priority for the content based on the metric related to the content, and queuing the content for crowdsourcing based on the priority determined from the metric.

Claims

1. A method of translating information using crowdsourcing, the method comprising:

evaluating a metric related to a content to be translated;

determining a priority for the content based on the metric related to the content;

queuing the content for the crowdsourcing based on the priority determined from the metric; and

translating, by a translation server, the information from a language to another language using the crowdsourcing,

wherein weights attached to the content to determine the priority of the content are constantly updated during a time period based on a current need of the content to be translated by counting a number of times a sentence is submitted for translation in the time period.

2. The method according to claim 1, wherein the metric includes a number of requests for translation during the time period.

3. The method according to claim 2, wherein the time period is based on a predetermined condition.

4. The method according to claim 1, further comprising collecting the metric related to the content to be translated based on a request for translation.

5. The method according to claim 4, wherein the metric includes a date of the request for translation.

6. The method according to claim 1, wherein the metric includes a user entered element.

7. The method according to claim 1, wherein the metric includes a translator expertise requirement.

8. The method according to claim 1, further comprising assigning the content from the queue to a translator based on the priority.

9. The method according to claim 1, further comprising assigning the content from the queue to a translator based on an expertise of the translator.

10. The method according to claim 1, wherein the metric includes a target language.

11. A non-transitory computer-readable medium tangibly embodying a program of machine-readable instructions executable by an apparatus to perform a method of translating information using crowdsourcing, the method comprising:

evaluating a metric related to a content to be translated;

determining a priority for the content based on the metric related to the content; and

queuing the content for crowdsourcing based on the priority determined from the metric; and

translating, by a translation server, the information from a language to another language using the crowdsourcing,

wherein weights attached to the content to determine the priority of the content are constantly updated during a time period based on a current need of the content to be translated by counting a number of times a sentence is submitted for translation in the time period.

12. The non-transitory computer-readable medium according to claim 11, wherein the metric includes a number of requests for translation during the time period.

13. The non-transitory computer-readable medium according to claim 11, further comprising collecting the metric related to the content to be translated based on a request for translation.

14. The non-transitory computer-readable medium according to claim 13, wherein the metric includes a date of the request for translation.

15. The non-transitory computer-readable medium according to claim 11, wherein the metric includes a user entered element.

16. The non-transitory computer-readable medium according to claim 11, wherein the metric includes a translator expertise requirement.

17. A translation system, comprising:

a processor of a computer adapted to receive content to be translated, the processor being configured so as to track a metric related to the content to be translated; and

a crowdsourcing data selector adapted to receive the content to be translated from the processor and queue the content to be translated based on the metric; and

a translation server that translates information from a language to another language based on results of crowdsourcing performed by the crowdsourcing data selector,

wherein weights attached to the content to determine a priority of the content are constantly updated during a time period based on a current need of the content to be translated by counting a number of times a sentence is submitted for translation in the time period.

18. The translation system according to claim 17, further comprising:

a translation buffer configured to store a human translation of the content to be translated; and

a crowdsourcing buffer configured to store the content to be translated.

19. The translation system according to claim 18, wherein the crowdsourcing data selector is configured so as to assign the content to be translated based on the metric and characteristic data of the user.

20. The translation system according to claim 18, wherein the processor is configured so as to receive the priority of the content by a user, and

wherein the metric comprises the priority of the content by the user.