Machine translation using global lexical selection and sentence reconstruction

1. A method comprising:

receiving a source phrase in a source language;

classifying the source phrase into a phrase meaning;

matching the phrase meaning to a target phrase automaton in a target language, the target phrase automaton comprising a plurality of states and a plurality of arcs interconnecting the plurality of states to define a sentence path, each of the plurality of states defining a word position slot for inserting a word from a bag of words, and each of the plurality of arcs associated with a pre-defined insertion cost for inserting the word from the bag of words based on a previous state in the sentence path, wherein the predefined insertion cost has one of a positive and negative value which is associated with one of penalizing and rewarding the sentence path based on how many words are in the sentence path in order to produce more words in a target sentence relative to the source phrase;

determining, for each word position slot in each target phrase automaton, a target word possibility from the bag of words associated with the word position slot based on at least one of a lexical translation of words in the source phrase and a phrase-to-phrase mapping;

calculating a target sentence probability for the sentence path based at least on the pre-defined insertion cost associated with each of the plurality of arcs for the sentence path; and

upon determining that the sentence path has a probability above a threshold, constructing the target sentence using the sentence path.

2. The method of claim 1 , wherein the target word possibility for each word position is weighted by a target language model.

3. The method of claim 1 , wherein the target word possibility for each word position is detected independently.

4. The method of claim 1 , further comprising:

adjusting a length of the target sentence by adding optional deletions when constructing the target sentence.

5. The method of claim 1 , wherein the determining for each word position slot of the target word possibility does not use information about previous words and subsequent words.

6. The method of claim 1 , wherein function words in the target word possibility of each word position serve as attributes on contentful lexical items.

7. The method of claim 6 , wherein the attributes are at least one of definiteness, tenses and case.

8. A system comprising:

a processor; and

a computer-readable storage medium storing instructions which, when executed by the processor, cause the processor to perform operations comprising:

receiving a source phrase in a source language;

classifying the source phrase into a phrase meaning;

matching the phrase meaning to a target phrase automaton in a target language, the target phrase automaton comprising a plurality of states and a plurality of arcs interconnecting the plurality of states to define a sentence path, each of the plurality of states defining a word position slot for inserting a word from a bag of words, and each of the plurality of arcs associated with a pre-defined insertion cost for inserting the word from the bag of words based on a previous state in the sentence path, wherein the predefined insertion cost has one of a positive and negative value which is associated with one of penalizing and rewarding the sentence path based on how many words are in the sentence path in order to produce more words in a target sentence relative to the source phrase;

determining, for each word position slot in each target phrase automaton, a target word possibility from the bag of words associated with the word position slot based on at least one of a lexical translation of words in the source phrase and a phrase-to-phrase mapping;

calculating a target sentence probability for the sentence path based at least on the pre-defined insertion cost associated with each of the plurality of arcs for the sentence path; and

upon determining that the sentence path has a probability above a threshold, constructing the target sentence using the sentence path.

9. The system of claim 8 , wherein the target word possibility for each word position is weighted by a target language model.

10. The system of claim 8 , wherein the target word possibility for each word position is detected independently.

11. The system of claim 8 , the computer-readable storage medium storing additional instructions which, when executed on the processor, perform a method further comprising:

adjusting a length of the target sentence by adding optional deletions when constructing the target sentence.

12. The system of claim 8 , wherein the determining for each word position slot of the target word possibility does not use information about previous words and subsequent words.

13. The system of claim 8 , wherein function words in the target word possibility of each word position serve as attributes on contentful lexical items.

14. The system of claim 13 , wherein the attributes are at least one of definiteness, tenses and case.

15. A computer-readable storage device having instructions stored which, when executed by a computing device, cause the computing device to perform operations comprising:

receiving a source phrase in a source language;

classifying the source phrase into a phrase meaning;

matching the phrase meaning to a target phrase automaton in a target language, the target phrase automaton comprising a plurality of states and a plurality of arcs interconnecting the plurality of states to define a sentence path, each of the plurality of states defining a word position slot for inserting a word from a bag of words, and each of the plurality of arcs associated with a pre-defined insertion cost for inserting the word from the bag of words based on a previous state in the sentence path, wherein the predefined insertion cost has one of a positive and negative value which is associated with one of penalizing and rewarding the sentence path based on how many words are in the sentence path in order to produce more words in a target sentence relative to the source phrase;

determining, for each word position slot in each target phrase automaton, a target word possibility from the bag of words associated with the word position slot based on at least one of a lexical translation of words in the source phrase and a phrase-to-phrase mapping;

calculating a target sentence probability for the sentence path based at least on the pre-defined insertion cost associated with each of the plurality of arcs for the sentence path; and

upon determining that the sentence path has a probability above a threshold, constructing the target sentence using the sentence path.

16. The computer-readable storage device of claim 15 , wherein the target word possibility for each word position is weighted by a target language model.

17. The computer-readable storage device of claim 15 , wherein the target word possibility for each word position is detected independently.

18. The computer-readable storage device of claim 15 , wherein the non-transitory computer-readable medium stores additional instructions which, when executed on the computing device, cause the computing device to perform operations further comprising:

adjusting a length of the target sentence by adding optional deletions when constructing the target sentence.

19. The computer-readable storage device of claim 15 , wherein the determining for each word position slot of the target word possibility does not use information about previous words and subsequent words.

20. The computer-readable storage device of claim 15 , wherein function words in the target word possibility of each word position serve as attributes on contentful lexical items.

21. The computer-readable storage device of claim 20 , wherein the attributes are at least one of definiteness, tenses and case.