Multi-lingual word hyphenation using inductive machine learning on training data
US-8996994-B2 · Mar 31, 2015 · US
US9262409B2 · US · B2
| Field | Value |
|---|---|
| Publication number | US-9262409-B2 |
| Application number | US-201213552601-A |
| Country | US |
| Kind code | B2 |
| Filing date | Jul 18, 2012 |
| Priority date | Aug 6, 2008 |
| Publication date | Feb 16, 2016 |
| Grant date | Feb 16, 2016 |
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Disclosed is a method for translating text fragments displayed on a screen from an input language into an output language and displaying the result. Translation may use electronic dictionaries, machine translation, natural language processing, control systems, information searches, (e.g., search engine via an Internet protocol), semantic searches, computer-aided learning, and expert systems. For a word combination, appropriate local or network accessible dictionaries are consulted. The disclosed method provides a translation in grammatical agreement in accordance with grammatical rules of the output language in consideration of the context of the text.
Opening claim text (preview).
We claim: 1. A computer-implemented method for translating a text fragment in an input language into an output language, the method comprising: receiving an indication of a selection of an area that includes text displayed on a screen of a device; identifying the text fragment based on the indication of the selection of the area that includes text; performing a dictionary lookup of the text fragment, wherein performing the dictionary lookup of the text fragment comprises: identifying several words in a left direction and identifying several words in a right direction from a base word of the text fragment; constructing combinations of the identified words with the base word; transforming each element of an array by inserting hyphens and space characters between portions of the base word and identified words; searching for each element of the array in an electronic dictionary; and searching for a linguistically similar word or word combination in an electronic dictionary; and providing an output of translation in a form that is in grammatical agreement with a context of the translated fragment using a morphologic synthesis; for each remaining untranslated portion of the text fragment for which a translation is not readily available, translating said untranslated portion of the text fragment based on a machine translation technique; and displaying the translation of the text fragment on the screen of the device, wherein the translation is displayed upon selecting the text fragment on the screen. 2. The method of claim 1 , wherein the identifying the text fragment includes performing an optical character recognition. 3. The method of claim 1 , wherein the translation alternatives are in a language different from the language of the text fragment. 4. The method of claim 1 , wherein selecting the text fragment may be done manually in a haptic-based or in a cursor-based manner. 5. The method of claim 1 , wherein identifying the text fragment includes identifying a sentence boundary or a paragraph boundary. 6. The method of claim 1 , wherein the method further comprises, prior to performing the dictionary lookup of the text fragment, identifying variants of the text fragment using linguistic descriptions and constructing a language-independent semantic structure to represent a meaning of a source sentence associated with the text fragment. 7. The method of claim 1 wherein performing the dictionary lookup further comprises selecting and using a translation dictionary for a given subject domain. 8. The method of claim 1 , wherein performing the dictionary lookup of the text fragment further comprises performing a morphological analysis for identifying a base form of words of the text fragment. 9. The method of claim 1 , wherein performing the dictionary lookup of the text fragment further comprises performing a morphological synthesis that determines grammatical forms of words in the text fragment and provides a grammatically agreed translation that is in grammatical agreement in accordance with grammatical rules of the output language. 10. The method of claim 1 , wherein performing the dictionary lookup of the text fragment further comprises selecting a variant of translation based on a most frequent usage or in accordance with a subject field of the source text. 11. The method of claim 1 , wherein performing the translation of the text fragment further comprises selecting and using a translation database, and wherein the translation database is derived from previous translation processes or segmentation of existing parallel texts. 12. The method of claim 1 , wherein performing the translation of the text fragment includes usage of terminology dictionaries for a given subject domain. 13. The method of claim 1 , wherein the machine translation technique includes a model-based machine translation technique, wherein the model-based machine translation technique comprises using linguistic descriptions to build a semantic structure to represent a meaning of each untranslated fragment, and wherein the method further comprises providing a syntactically coherent translation. 14. The method of claim 1 , wherein the displaying the translation of the text fragment comprises displaying a translation in the form of one of a pop-up window, a superscript text, a subscript text, and a text balloon. 15. A device for translating a text fragment in an input language into an output language, the device comprising: a processor; a memory in electronic communication with the processor, wherein the memory is configured with instructions to cause the processor to perform actions comprising: receiving an indication of a selection of an area that includes text displayed on a screen of a device; identifying the text fragment based on the indication of the selection of the area that includes text; performing a dictionary lookup of the text fragment, wherein performing the dictionary lookup of the text fragment comprises: identifying several words in a left direction and identifying several words in a right direction from base words of the text fragment; constructing combinations of the identified words with base words; transforming each element of an array by inserting hyphens and space characters between portions of the base words and identified words; searching for each element of the array in an electronic dictionary; and searching for a linguistically similar word or word combination in an electronic dictionary; and providing output of translation in a form that is in grammatical agreement with a context of the translated fragment using a morphologic synthesis; for each portion of the text fragment for which a translation is readily available, translating said portion of the text fragment based on said readily available translation; for each remaining untranslated portion of the text fragment for which a translation is not readily available, translating said untranslated portion of the text fragment based on a machine translation technique; and displaying the translation of the text fragment on the screen of the device, wherein the translation is displayed upon selecting the text fragment on the screen. 16. The device of claim 15 , wherein selecting text fragment may be done manually in a haptic-based or in a cursor-based manner. 17. The device of claim 15 , wherein identifying the text fragment includes identifying a sentence boundary or a paragraph boundary. 18. The device of claim 15 , wherein dictionary lookup includes selecting the translation dictionary for a given subject domain. 19. The device of claim 15 , wherein performing the dictionary lookup of the text fragment includes morphological analysis for identifying a base form of words of the text fragment. 20. The device of claim 15 , wherein performing the dictionary lookup of the text fragment includes performing a morphological synthesis that determines a grammatical form of words in the text fragment, and wherein the method further comprises providing a translation that is in grammatical agreement with grammatical rules of the output language. 21. The device of claim 15 , wherein performing the dictionary lookup of the text fragment includes selecting a variant of translation based on a frequency of use or in accordance with a topic field of the source text. 22. The device of claim 15 , wherein performing the translation of the text fragment includes selection and use of a translation database, and wherein the trans
Semantic analysis · CPC title
Rule-based translation · CPC title
Morphological analysis · CPC title
Lexical analysis, e.g. tokenisation or collocates · CPC title
Automatic line break hyphenation · CPC title
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