| Machine Translation(MT) is the process to convert one natural language to another taking use of PC,which is a category of Computer Linguistics [1]. MT's origin beginning is back about 80 years ago, and with the ups and downs in its history, most of the MT software designers still dependent on Statistics excessively as the ground of translation strategy, instead of using theory of linguistics scientifically, so that the result outputs of existing MT software are inevitably mixed with misconception and incompleteness for grammar and semantic. Furthermore, the issue of that accuracy and efficiency of MT cannot be both considered thoughtfully is still on the table.The"Dependence Tree"and the"Case Grammar"will be used as the theoretical foundation of our MT software, which has a supplement of corpus with abundant details of morphemes'properties. The Method of Conversion Translation and the Method of Direct Translation are combined together realized by combining two different-complexity- level ways of the translation. Simply speaking, we build the"Verb Truck"analysis system based on the theory of"Dependence Tree"as well as the phrase structure analysis system in view of"Case Grammar"to accomplish the transformation from"Source Language (SL)"to"Target Language (TL)", at the same time, the corpus will become the resources for translating directly from SL to TL by just replacing the words of SL with the corresponding ones in the corpus. The emphasis of our software is interpreting complicated Chinese sentences into English, especially those formal sentences of standard grammar and common idioms, by processing and analyzing Chinese sentences according to Syntactic and Word Formation.The overall strategy of this software is calling function modules in sequence of structure of"Dependence Tree"to upgrade the whole sentence from being composed of morphemes as the mini units to being consist of integral ingredients as parts of the sentence. After that the"Verb Truck"analysis module will be called, to obtain the whole orderliness of the sentence and the final English output via the"Case Frame"mapping relationship of every verb and its dominated structures and the influence of the latter to the former.Based on all the explication given above, we can achieve satisfying translation result of some complex sentences and we also make a pretty smooth convergence of the three steps of conversion. Additionally, the integration of analysis and interpreting cuts down the need of buffer greatly and also improve efficiency. |
