Extraction-empowered machine translation

• US 8,131,536 B2
• Filed: 11/30/2007
• Issued: 03/06/2012
• Est. Priority Date: 01/12/2007
• Status: Active Grant

• Current Assignee: Raytheon BBN Technlogies Corp. (Rtx Corporation)
• Original Assignee: Raytheon BBN Technlogies Corp. (Rtx Corporation)
• Inventors: Weischedel, Ralph M., Xu, Jinxi, Kayser, Michael R.
• Primary Examiner(s): Neway, Samuel G
• Application Number:
  US11/998,663
• Publication Number:
  US 20080215309A1
• Time in Patent Office: 1,558 Days
• Field of Search: 704 1- 8
• US Class Current: 704/5
• CPC Class Codes: G06F 40/131 Fragmentation of text files, e.g. creating reusable text-blocks; Linking to fragments, e.g. using XInclude; Namespaces
• CPC Class Codes: G06F 40/295 Named entity recognition
• 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

The invention relates to systems and methods for automatically translating documents from a first language to a second language. To carry out the translation of a document, elements of information are extracted from the document and are translated using one or more specialized translation processes. The remainder of the document is separately translated by a statistical translation process. The translated elements of information and the translated remainder are then merged into a final translated document.

Claims

1. A method for automatically translating a document from a first language to a second language comprising:

receiving the document in the first language;

processing the document to extract elements of information;

determining, using a processor, a plurality of potential translations for each of the extracted elements of information using a first translation process and a likelihood value for each of the potential translations of the elements of information;

determining a plurality of potential translations of a remainder of the document using a second, different translation process and a likelihood value for each potential remainder translation;

generating a plurality of combinations by combining a plurality of the potential translations of the elements of information with a plurality of the potential remainder translations;

determining a likelihood value for respective ones of a plurality of the combinations based on a model of the second language and corresponding likelihood values of each of the potential element of information translations and remainder translations included in the respective combinations; and

forming a translated version of the document based on the likelihood values of the combinations.

2. The method of claim 1, wherein the elements of information comprise names of named entities, and the first translation process comprises a transliteration process.

3. The method of claim 1, wherein the first translation process further comprises at least one of a statistical translation process, a transfer rule-based translation process, and an application of a bilingual name lexicon depending on a semantic type of the named entities.

4. The method of claim 1, wherein the elements of information comprise at least of one of dates, times, and amounts, and the first translation process comprises applying semantic rules for the second language associated with a corresponding class of information.

5. The method of claim 1, wherein the elements of information comprise core noun phrase descriptions and the first translation process comprises employing a mixture model to translate the extracted elements of information.

6. The method of claim 5, wherein employing the mixture model includes employing a statistical translation process combined with a dictionary translation process.

7. The method of claim 1, wherein the first translation process includes applying syntactic and semantic transfer rules.

8. The method of claim 1, wherein the second translation process includes employing a statistical translation process.

9. The method of claim 1, further comprising

identifying a span of at least two words that are related, and

translating the words of the span as a cluster.

10. The method of claim 1, wherein the remainder of the document, prior to translation, includes placeholders for original locations of the extracted elements of information.

11. The method of claim 10, wherein the translated remainder of the document includes placeholders for insertion of the translated elements of information.

12. A method for automatically translating a document from a first language to a second language comprising:

receiving the document in the first language;

determining, using a processor, a plurality of potential translations of a first portion of the document to the second language using a first translation process and a likelihood value for each potential first portion translation;

determining a plurality of potential translations of a second portion of the document to the second language using a second, different translation process and a likelihood value for each potential second portion translation;

generating a plurality of combinations by combining a plurality of the potential translations of the first portion with a plurality of the potential translations of the second portion;

determining a likelihood value for respective ones of a plurality of the combinations based on a model of the second language and corresponding likelihood values of each of the potential translations of the first portion and the potential translations of the second portion; and

forming a translated version of the document based on the likelihood values of the combinations.

13. The method of claim 12, comprising:

extracting the first portion from the document; and

replacing the first portion in the document with placeholders to form the second portion.

14. The method of claim 12, wherein the first translation process is at least partially rule driven and the second translation process is statistics-based.

15. A system for automatically translating a document from a first language to a second language comprising:

a first processor for receiving the document in the first language and processing the document to extract elements of information;

a second processor for determining a plurality of potential translations for each of the extracted elements of information using a first translation process and a likelihood value for each of the potential translations of the elements of information;

a third processor for determining a plurality of potential translations of a remainder of the document using a second, different translation process and a likelihood value for each potential remainder translation;

a fourth processor for generating a plurality of combinations by combining a plurality of the potential translations of the elements of information with a plurality of the potential remainder translations;

a fifth processor for determining a likelihood value for respective ones of a plurality of the combinations based on a model of the second language and corresponding likelihood values of each of the potential element of information translations and remainder translations included in the respective combinations; and

a sixth processor for forming a translated version of the document based on the likelihood values of the combinations.

16. A non-transitory computer-readable medium containing computer-executable instructions, which when executed by a computer carry out a method for translating a document from a first language to a second language, comprising:

receiving the document in the first language;

processing the document to extract elements of information;

determining, using a processor, a plurality of potential translations for each of the extracted elements of information using a first translation process and a likelihood value for each of the potential translations of the elements of information;

determining a plurality of potential translations of a remainder of the document using a second, different translation process and a likelihood value for each potential remainder translation;

generating a plurality of combinations by combining a plurality of the potential translations of the elements of information with a plurality of the potential remainder translations;

determining a likelihood value for respective ones of a plurality of the combinations based on a model of the second language and corresponding likelihood values of each of the potential element of information translations and remainder translations included in the respective combinations; and

forming a translated version of the document based on the likelihood values of the combinations.