1. Automatic input editing2. Automatic segmentation3. Syntactical analysis4. Transformation with output editing
   Japanese Characteristics    › No spaces    › Kanas and Kanjis   Thus, requires    › Automatically cutting into compon...
   Each kana will be Romanized    › To preserve       one-to-one correspondence between kanas and        their correspon...
   Segmentation of a continuous run of    tokens    › Based on following prospects:       Auxiliary items will be shorte...
   Predictive analysis:    › Originally by Rhodes   Peculiarity seen in Japanese :    › More convenient to start from en...
   Each word in a sentence will be assigned    › An essence which has been fulfilled by it    › A linkage number which sh...
   例)ネズミがネコを殺した話は私を驚かせた.
   This stage deals with the synthesis of the TL   Brief explanation:    › Words with same group num. are gathered    › ...
   Readings in Machine Translation    › Edited by Sergei Nirenburg, Harold Somers,      and Yorick Wilks    › The MIT Press
Approach to japanese english automatic translation by Susumu Kuno
Approach to japanese english automatic translation by Susumu Kuno
Approach to japanese english automatic translation by Susumu Kuno
Approach to japanese english automatic translation by Susumu Kuno
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Approach to japanese english automatic translation by Susumu Kuno

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Japanese English Automatic Translation Approach by Susumu Kuno

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Approach to japanese english automatic translation by Susumu Kuno

  1. 1. 1. Automatic input editing2. Automatic segmentation3. Syntactical analysis4. Transformation with output editing
  2. 2.  Japanese Characteristics › No spaces › Kanas and Kanjis Thus, requires › Automatically cutting into components However, to prevent too much sized dictionary › Regulations can be set  Kana texts in which no kanjis are used  Kana-kanji texts in which kanjis are used wherever possible according to the official directives about the use of kana and kanjis. › This is “pre-editing”
  3. 3.  Each kana will be Romanized › To preserve  one-to-one correspondence between kanas and their correspondent Roman letters › Better analyzed with Roman letters than kanas  Fewer varieties of suffixes  Fewer rules of permissible combinations with canonical stems  Fewer possibilities of homographic verbal stems Kanji will be replaced with irreducible unit token › No kanji will contain more than one “morpheme”
  4. 4.  Segmentation of a continuous run of tokens › Based on following prospects:  Auxiliary items will be shorter in length and fewer in number  No problem will be caused by:  assuming every “phrase” in a sentence begins with a dictionary item  including “prefixes” in the category of dictionary items
  5. 5.  Predictive analysis: › Originally by Rhodes Peculiarity seen in Japanese : › More convenient to start from end of sentence:  Words having a final position in a sentence are limited  Particles which show case, prepositional or conjunctional relationships always follow words, phrases or clauses to which they are attached  Attributive words, phrases and clauses always stand before DT substantives which they modify
  6. 6.  Each word in a sentence will be assigned › An essence which has been fulfilled by it › A linkage number which shows by which word it has been predicted › A group number which shows to which clause in the sentence it belongs Another peculiarity about Japanese: › The subject of a sentence is very often omitted Hence, in this analysis: › Subject market and relative subject marker predictions is essential
  7. 7.  例)ネズミがネコを殺した話は私を驚かせた.
  8. 8.  This stage deals with the synthesis of the TL Brief explanation: › Words with same group num. are gathered › Transformation of word order is performed In concrete: › Subject marker, object marker & relative subject marker are omitted › Subject master or relative subject master comes first within each group › followed by predicate head or relative predicate head › and then by object master
  9. 9.  Readings in Machine Translation › Edited by Sergei Nirenburg, Harold Somers, and Yorick Wilks › The MIT Press

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