TRANSLATED SENTENCE QUALITY ESTIMATION

• US 20120209590A1
• Filed: 02/16/2011
• Published: 08/16/2012
• Est. Priority Date: 02/16/2011
• Status: Abandoned Application

• Current Assignee: International Business Machines Corporation
• Original Assignee: International Business Machines Corporation
• Inventors: Wu, Cheng, Huerta, Juan M.
• Application Number:
  US13/028,555
• Publication Number:
  US 20120209590A1
• Time in Patent Office: Days
• US Class Current: 704/7
• CPC Class Codes: G06F 40/44 Statistical methods, e.g. probability models
• CPC Class Codes: G06F 40/51 Translation evaluation

Abstract

A method, system, and computer readable storage medium including a computer readable program are provided. The method includes storing a set of sentences in a memory device. The method further includes receiving an input translated phrase and searching the set of sentences for a subset of sentences closest to the input translated phrase based on a set of respective distances to the sentences in the set with respect to the input translated phrase. The method also includes calculating and outputting a language model score for the subset of sentences based on a function of a subset of respective distances pertaining to the subset of sentences.

Claims

1. A method comprising:

storing a set of sentences in a memory device;

receiving an input translated phrase and searching the set of sentences for a subset of sentences closest to the input translated phrase based on a set of respective distances to the sentences in the set with respect to the input translated phrase; and

calculating and outputting a language model score for the subset of sentences based on a function of a subset of respective distances pertaining to the subset of sentences.

2. The method of claim 1, wherein the sentence retriever searches for the subset of sentences using respective string edit distances to the sentences in the set with respect to the input translated phrase.

3. The method of claim 1, wherein the language model score is calculated to mimic a probability of the input translated phrase given the set of sentences.

4. The method of claim 1, wherein the set of sentences is sub-sampled to provide a sub-sampled set of sentences from which the subset of sentences is determined by said sentence retriever.

5. The method of claim 1, wherein the input translated phrase is a machine translation engine output.

6. The method of claim 1, wherein the input translated phrase is a result of an automated process.

7. The method of claim 1, wherein the input translated phrase is a result of a human post-editing a machine translation engine output.

8. The method of claim 1, wherein the text of the input translated phrase is segmented to obtain a plurality of segments, and wherein the plurality of segments are used in place of the sentences in the set to determine a group of respective distances from the plurality of segments with respect to the input translated phrase, and wherein the language model score is calculated with respect to the group of respective distances.

9. The method of claim 8, wherein a final language model score that is output is a function of respective scores of the individual segments in the plurality of segments.

10. The method of claim 1, wherein the language model score comprises one of a single score for all of the sentences in the subset and a plurality of individual scores, with each of the plurality of individual scores corresponding to a respective one of the sentences in the subset.

11. A system comprising:

a memory device for storing a set of sentences;

a sentence retriever coupled to said memory device for receiving an input translated phrase and searching the set of sentences for a subset of sentences closest to the input translated phrase based on a set of respective distances to the sentences in the set with respect to the input translated phrase; and

a quality score computer coupled to said sentence retriever for receiving the subset of sentences and a subset of respective distances pertaining to the subset of sentences, and calculating and outputting a language model score for the subset of sentences based on a function of the subset of respective distances.

12. The system of claim 11, wherein the sentence retriever searches for the subset of sentences using respective string edit distances to the sentences in the set with respect to the input translated phrase.

13. The system of claim 11, wherein the language model score is calculated to mimic a probability of the input translated phrase given the set of sentences.

14. The system of claim 11, wherein the set of sentences is sub-sampled to provide a sub-sampled set of sentences from which the subset of sentences is determined by said sentence retriever.

15. The system of claim 11, wherein the input translated phrase is a machine translation engine output or a result of a human post-editing the machine translation engine output.

16. The system of claim 11, wherein the input translated phrase is a result of an automated process.

17. The system of claim 11, wherein the text of the input translated phrase is segmented to obtain a plurality of segments, and wherein the plurality of segments are used in place of the sentences in the set to determine a group of respective distances from the plurality of segments with respect to the input translated phrase, and wherein the language model score is calculated with respect to the group of respective distances.

18. The system of claim 17, wherein a final language model score that is output from said quality computer is a function of respective scores of the individual segments in the plurality of segments.

19. The system of claim 11, wherein the language model score comprises one of a single score for all of the sentences in the subset and a plurality of individual scores, with each of the plurality of individual scores corresponding to a respective one of the sentences in the subset.

20. A computer readable storage medium comprising a computer readable program, wherein the computer readable program when executed on a computer causes the computer to perform the following:

storing a set of sentences in a memory device;

receiving an input translated phrase and searching the set of sentences for a subset of sentences closest to the input translated phrase based on a set of respective distances to the sentences in the set with respect to the input translated phrase; and

calculating and outputting a language model score for the subset of sentences based on a function of a subset of respective distances pertaining to the subset of sentences.