CN108153743A - Intelligent offline translation machine based on similarity - Google Patents
Intelligent offline translation machine based on similarity Download PDFInfo
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- CN108153743A CN108153743A CN201810064998.XA CN201810064998A CN108153743A CN 108153743 A CN108153743 A CN 108153743A CN 201810064998 A CN201810064998 A CN 201810064998A CN 108153743 A CN108153743 A CN 108153743A
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- G06F40/58—Use of machine translation, e.g. for multi-lingual retrieval, for server-side translation for client devices or for real-time translation
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Abstract
A kind of intelligent offline translation machine based on similarity of offer of the present invention, particularly Chinese is to the intelligent offline translation machine based on similarity of English, pass through the reasonable segmentation to Chinese sentence, phase recency calculates, English create-rule, obtains satisfactory English, and network data base need not be relied on to a certain extent by realizing, only by handling Chinese sentence to be translated, accurate translation result can be also obtained in combination with the English Translation rule of setting.
Description
Technical field
The invention belongs to automatic translation fields, and in particular to a kind of intelligent offline translation machine based on similarity.
Background technology
With the development of smart machine, intelligent operating system is also more and more diversified, such as the IOS of Apple Inc., Google
The Android of company, the Firefox OS of red fox company etc., and the smart machine for being integrated with these systems is also begun to by more next
More users uses, and user is played using these equipment, social, reading etc. daily routines.
And more and more opening with society, people read there are also more chances and are not belonging to oneself mother tongue
Content, whether usually hobby reads or because of academic program, work requirements etc., can usually encounter many foreign language datas, mesh
Method on preceding smart machine there are most common inquiring foreign language vocabulary is to open foreign language inquiry application manually by user, defeated manually
Enter word enquiring, the better application ratio slightly done is if any road dictionary.Currently a popular automatic translating method mainly has three classes, the
One kind is word-based, using word as the base unit of translation, does not consider that contextual information and human language are gained knowledge, translates
When, the target language word corresponding to each original language word is first looked for, is inserted into, delete target language word, and adjust
They whole sequence is combined into target language sentence, and feature is that translation virtuality is fast, but accuracy is poor, and the second class is based on short
The translation of language, translation granularity expand to phrase from word, preferably solve local context Dependence Problem, greatly improve the stream of translation
Sharp degree and accuracy rate, third class are the translations based on syntax, and syntactic structure information is introduced translation process, but need grammer knot
Structure knowledge introduces, and needs to adjust original language word order using syntactic knowledge before translation, utilizes syntactic knowledge after translation
It reorders.
For at present, in existing automatic translation by computer, the translation of third class is trend, however to obtain preferable translation
Effect obtains syntactic structure preferably by the mode networked online, in addition, the translation speed is also relatively slow.Although internet is
Obtained it is great commonly used, however, with the variation of environment and the appearance of various temporary conditions, our intelligence is set
It is standby at every moment to keep presence, therefore, it is badly in need of a kind of intelligent offline translation machine based on similarity, as far as possible
It realizes in the case of being detached from network, can also obtain accurate translation result.
Invention content
In view of above analysis, it is a primary object of the present invention to provide a kind of intelligence based on similarity for overcoming drawbacks described above
Energy offline translation machine, particularly Chinese pass through the conjunction to Chinese sentence to the intelligent offline translation machine based on similarity of English
Reason segmentation, phase recency calculate, and English create-rule obtains satisfactory English, and net need not be relied on to a certain extent by realizing
Network database only by handling Chinese sentence to be translated, is obtained in combination with the English Translation rule technical ability of setting
Accurate translation result.
The purpose of the present invention is what is be achieved through the following technical solutions.
A kind of intelligent offline translation machine based on similarity, which is characterized in that including：
For receiving the Chinese sentence of input, word segmentation is carried out according to Chinese-English dictionary, is obtained correct for chinese input module
Word segmentation form；
Phase recency computing module, for using certain features of Chinese sentence to be translated as in querying condition to database
Similar sentence is inquired, and immediate sentence is selected according to close degree size, is i.e. phase recency calculates；
Alignment module, for the alignment rule according to setting, the sentence being aligned in Chinese sentence and database to be translated,
And the word of the word of Chinese sentence and english sentence in align data library；
Translation module for the English Translation rule according to setting, translates into satisfactory English.
Further, the word segmentation the specific steps are (1) sets the length of sentence to be split as L, in dictionary most
Big word length is M, and the character string that length is taken to be M since first character to be split is matched.(2) if can match,
Then using this character string as a word, divide from sentence, using the part at left and right sides of the word as new sentence, continue
This process is repeated to be split；(3) if cannot match, continue the character string that length is taken to be M from second word of sentence and carry out
Matching；(4) if cannot match, successively since in sentence third, the 4th ... take the length to be (L-M+1) a word
The character string of M is matched, if successful match, is returned to (2) step, if cannot all match, is shown without length
For the word of M, this season M-1, then with this string length, since first character, matched；(5) it repeats the above process,
Until the word in sentence all complete by segmentation.
Further, it after the completion of word segmentation, further includes and part-of-speech tagging and special word processing is carried out to segmentation result,
Part of speech ambiguity is eliminated using the semantic information and rule of semantic database, improves part-of-speech tagging accuracy rate.
Further, the phase recency calculating is included in sentence more to be translated in overall structure, extracts language to be translated
The feature of sentence, sentence similar in database search is removed by the feature of extraction.
Further, the feature includes comparing part of speech, semanteme, and the connection including calculating semantic distance and word is closed
System.
Further, the alignment includes setting the segmentation form of the Chinese example sentence in database, according in Chinese example sentence
Chinese example sentence translation, is divided into form corresponding with Chinese terms, while store Chinese-English contrast relationship by the appearance sequence of word,
During alignment, with reference to word length and above-mentioned phase recency result of calculation, consolidated according to the translation that the frequency of occurrences in Chinese-English dictionary is higher
Vocabulary is determined as node, is aligned according to contrast relationship in database.
Further, it is described translate into satisfactory English and specifically include translated according to above-mentioned alignment result, such as
Fruit sentence to be translated is identical with the corresponding word string of example sentence corresponding in database, then directly by the translation result in example sentence
It is repeated, if sentence to be translated is different from the corresponding word string of example sentence corresponding in database, with to be translated
The word that translation word in sentence corresponding to word goes to replace example sentence translation is worked as and is treated in the appropriate location for copying to new translation
When cypher text is a word of multiple word alignment example sentences, then multiple words to be translated are first translated, then to be translated
Multiple words replace the part that is aligned in example sentence translation as a whole, and the multiple word is translated as using the multiple
Similar lexical translation is as a result, using the result as the translation result of multiple word in word inquiry database.
Technical scheme of the present invention has the following advantages：
Overcome dependence of the above-mentioned translation on line to network data base, only by handling Chinese sentence to be translated,
A kind of particularly Chinese is provided to the intelligent offline translation machine based on similarity of English, passes through rationally dividing to Chinese sentence
It cuts, phase recency calculates, and accurate translation result can be also obtained in combination with the English Translation rule of setting.
Description of the drawings
Fig. 1 shows the composition frame chart of translator according to the preferred embodiment of the invention.
Specific embodiment
As shown in Figure 1, a kind of intelligent offline translation machine based on similarity, including：
For receiving the Chinese sentence of input, word segmentation is carried out according to Chinese-English dictionary, is obtained correct for chinese input module
Word segmentation form；
Phase recency computing module, for using certain features of Chinese sentence to be translated as in querying condition to database
Similar sentence is inquired, and immediate sentence is selected according to close degree size, is i.e. phase recency calculates；
Alignment module, for the alignment rule according to setting, the sentence being aligned in Chinese sentence and database to be translated,
And the word of the word of Chinese sentence and english sentence in align data library；
Translation module for the English Translation rule according to setting, translates into satisfactory English.
The word segmentation the specific steps are (1) sets the length of sentence to be split as L, and maximum word is long in dictionary
It spends for M, the character string that length is taken to be M since first character to be split is matched.(2) if can match, by this word
Symbol string is divided from sentence as a word, using the part at left and right sides of the word as new sentence, continues to repeat this mistake
Journey is split；(3) if cannot match, the character string for from second word of sentence continuing that length is taken to be M is matched；(4)
If cannot match, successively since in sentence third, the 4th ... the character that length is M is taken (L-M+1) a word
String is matched, if successful match, returns to (2) step, if cannot all match, is shown without word of the length for M
Language, this season M-1, then with this string length, since first character, matched；(5) it repeats the above process, until language
Word in sentence all complete by segmentation.
After the completion of word segmentation, further include and part-of-speech tagging and special word processing are carried out to segmentation result, utilize semanteme
The semantic information and rule of database eliminate part of speech ambiguity, improve part-of-speech tagging accuracy rate.
The phase recency calculating is included in sentence more to be translated in overall structure, extracts the feature of sentence to be translated,
Sentence similar in database search is gone by the feature of extraction.
The feature includes comparing part of speech, semanteme, the connection relation including calculating semantic distance and word.
The alignment includes setting the segmentation form of the Chinese example sentence in database, according to the appearance of word in Chinese example sentence
Sequentially, Chinese example sentence translation is divided into form corresponding with Chinese terms, while stores Chinese-English contrast relationship, during alignment, knot
Word length and above-mentioned phase recency result of calculation are closed, vocabulary conduct is fixed according to the higher translation of the frequency of occurrences in Chinese-English dictionary
Node is aligned according to contrast relationship in database.
It is described translate into satisfactory English and specifically include translated according to above-mentioned alignment result, if to be translated
Sentence is identical with the corresponding word string of example sentence corresponding in database, then directly repeats the translation result in example sentence,
If sentence to be translated is different from the corresponding word string of example sentence corresponding in database, with word in sentence to be translated
Corresponding translation word removes the word instead of example sentence translation in the appropriate location for copying to new translation, and when text to be translated is
During one word of multiple word alignment example sentences, then multiple words to be translated are first translated, then multiple words to be translated
As a whole instead of the part being aligned in example sentence translation, and the multiple word be translated as inquire number using the multiple word
According to lexical translation similar in library as a result, using the result as the translation result of multiple word.
Technical scheme of the present invention has the following advantages：
Overcome dependence of the above-mentioned translation on line to network data base, only by handling Chinese sentence to be translated,
A kind of particularly Chinese is provided to the intelligent offline translation machine based on similarity of English, passes through rationally dividing to Chinese sentence
It cuts, phase recency calculates, and accurate translation result can be also obtained in combination with the English Translation rule of setting.
The foregoing is merely illustrative of the preferred embodiments of the present invention, is not intended to limit the invention, all essences in the present invention
All any modification, equivalent and improvement made within refreshing and principle etc., should all be included in the protection scope of the present invention.
Claims (7)
1. a kind of intelligent offline translation machine based on similarity, which is characterized in that including：
Chinese input module for receiving the Chinese sentence of input, carries out word segmentation according to Chinese-English dictionary, obtains correct word
Language divides form；
Phase recency computing module, for using certain features of Chinese sentence to be translated as being inquired in querying condition to database
Go out similar sentence, and immediate sentence is selected according to close degree size, is i.e. phase recency calculates；
Alignment module, for the alignment rule according to setting, the sentence being aligned in Chinese sentence and database to be translated, and
The word of the word of Chinese sentence and english sentence in align data library；
Translation module for the English Translation rule according to setting, translates into satisfactory English.
2. a kind of intelligent offline translation machine based on similarity as described in claim 1, wherein the word segmentation is specific
Step is that (1) sets the length of sentence to be split as L, and maximum word length is M in dictionary, is opened from first character to be split
The character string for beginning that length is taken to be M is matched.(2) if can match, using this character string as a word, divide from sentence
It cuts, using the part at left and right sides of the word as new sentence, repeatedly this process that continues is split；(3) if cannot match,
The character string for from second word of sentence continuing that length is taken to be M is matched；(4) if cannot match, successively from sentence
The character string that third, the 4th ... (L-M+1) a word start that length is taken to be M is matched, if successful match, is returned
(2) step if cannot all match, shows without the word that length is M, this season M-1, then long with this character string
Degree, since first character, is matched；(5) it repeats the above process, until the word in sentence all complete by segmentation.
3. a kind of intelligent offline translation machine based on similarity as claimed in claim 2, wherein after the completion of word segmentation, is also wrapped
It includes and part-of-speech tagging and special word processing is carried out to segmentation result, word is eliminated using the semantic information and rule of semantic database
Property ambiguity, improve part-of-speech tagging accuracy rate.
4. a kind of intelligent offline translation machine based on similarity as described in claim 1, the phase recency calculating is included in total
Sentence more to be translated in body structure, extracts the feature of sentence to be translated, goes database search close by the feature of extraction
Sentence.
5. a kind of intelligent offline translation machine based on similarity as claimed in claim 4, the feature includes comparing part of speech, language
Justice, the connection relation including calculating semantic distance and word.
6. a kind of intelligent offline translation machine based on similarity as described in claim 1, the alignment includes setting database
In Chinese example sentence segmentation form, according to the appearance sequence of word in Chinese example sentence, Chinese example sentence translation is divided into and Chinese
During alignment, knot is calculated with reference to word length and above-mentioned phase recency for the corresponding form of word, while store Chinese-English contrast relationship
Fruit fixes vocabulary as node according to the higher translation of the frequency of occurrences in Chinese-English dictionary, is carried out according to contrast relationship in database
Alignment.
7. a kind of intelligent offline translation machine based on similarity as claimed in claim 2, described to translate into satisfactory English
Text is specifically included to be translated according to above-mentioned alignment result, if sentence to be translated is opposite with example sentence corresponding in database
The word string answered is identical, then directly repeats the translation result in example sentence, if opposite in sentence and database to be translated
The corresponding word string of example sentence answered is different, then is gone that example sentence is replaced to translate with the translation word corresponding to word in sentence to be translated
Word in the appropriate location for copying to new translation, and when text to be translated be multiple word alignment example sentences a word when,
Multiple words to be translated are then first translated, then multiple words to be translated are replaced as a whole the portion being aligned in example sentence translation
Point, and the multiple word be translated as using similar lexical translation in the multiple word inquiry database as a result, with
Translation result of the result as multiple word.
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN111611811A (en) * | 2020-05-25 | 2020-09-01 | 腾讯科技（深圳）有限公司 | Translation method, translation device, electronic equipment and computer readable storage medium |
Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN1652106A (en) * | 2004-02-04 | 2005-08-10 | 北京赛迪翻译技术有限公司 | Machine translation method and apparatus based on language knowledge base |
| US20120232882A1 (en) * | 2009-08-14 | 2012-09-13 | Longbu Zhang | Method for patternized record of bilingual sentence-pair and its translation method and translation system |
| CN106874263A (en) * | 2017-01-17 | 2017-06-20 | 中译语通科技（北京）有限公司 | A kind of Sino-British corpus proofreading method based on multi-dimensional data analysis and semanteme |
-
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Patent Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN1652106A (en) * | 2004-02-04 | 2005-08-10 | 北京赛迪翻译技术有限公司 | Machine translation method and apparatus based on language knowledge base |
| US20120232882A1 (en) * | 2009-08-14 | 2012-09-13 | Longbu Zhang | Method for patternized record of bilingual sentence-pair and its translation method and translation system |
| CN106874263A (en) * | 2017-01-17 | 2017-06-20 | 中译语通科技（北京）有限公司 | A kind of Sino-British corpus proofreading method based on multi-dimensional data analysis and semanteme |
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| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111611811A (en) * | 2020-05-25 | 2020-09-01 | 腾讯科技（深圳）有限公司 | Translation method, translation device, electronic equipment and computer readable storage medium |
| CN111611811B (en) * | 2020-05-25 | 2023-01-13 | 腾讯科技（深圳）有限公司 | Translation method, translation device, electronic equipment and computer readable storage medium |
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Denomination of invention: Intelligent Offline Translation Machine Based on Similarity Effective date of registration: 20230921 Granted publication date: 20211217 Pledgee: Zhongguancun Beijing technology financing Company limited by guarantee Pledgor: Jiaguyi (Beijing) Language Technology Co.,Ltd. Registration number: Y2023990000471 |