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Example-based machine translation (EBMT) is a method of machine translation often characterized by its use of a bilingual corpus with parallel texts as its main knowledge base at run-time. It is essentially a translation by analogy and can be viewed as an implementation of a case-based reasoning approach to machine learning .
Figure 1. Demonstration of the languages which are used in the process of translating using a bridge language. Interlingual machine translation is one of the classic approaches to machine translation. In this approach, the source language, i.e. the text to be translated is transformed into an interlingua, i.e., an abstract language-independent ...
The representation of a grammar is a set of syntax diagrams. Each diagram defines a "nonterminal" stage in a process. There is a main diagram which defines the language in the following way: to belong to the language, a word must describe a path in the main diagram. Each diagram has an entry point and an end point.
A DMT system is designed for a specific source and target language pair and the translation unit of which is usually a word. Translation is then performed on representations of the source sentence structure and meaning respectively through syntactic and semantic transfer approaches. A transfer-based machine translation system involves three ...
The only interlingual machine translation system that was made operational at the commercial level was the KANT system (Nyberg and Mitamura, 1992), which was designed to translate Caterpillar Technical English (CTE) into other languages.
Example of a system context diagram. [1] A system context diagram in engineering is a diagram that defines the boundary between the system, or part of a system, and its environment, showing the entities that interact with it. [2] This diagram is a high level view of a system. It is similar to a block diagram.
The translation is generated from this representation using both bilingual dictionaries and grammatical rules. It is possible with this translation strategy to obtain fairly high quality translations, with accuracy in the region of 90% [ vague ] (although this is highly dependent on the language pair in question, for example the distance ...
An example of a word-based translation system is the freely available GIZA++ package , which includes the training program for IBM models and HMM model and Model 6. [7] The word-based translation is not widely used today; phrase-based systems are more common. Most phrase-based systems are still using GIZA++ to align the corpus [citation needed].