page_title: Interlingual machine translation
section_title: Translation process
hierarchical_section_title: Interlingual machine translation / Translation process
caption_attribution_description: Figura 4: Proceso de traducción en un sistema basado en el conocimiento.
context_page_description: 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 representation. The target language is then generated from the interlingua. Within the rule-based machine translation paradigm, the interlingual approach is an alternative to the direct approach and the transfer approach.
  In the direct approach, words are translated directly without passing through an additional representation. In the transfer approach the source language is transformed into an abstract, less language-specific representation. Linguistic rules which are specific to the language pair then transform the source language representation into an abstract target language representation and from this the target sentence is generated.
  The interlingual approach to machine translation has advantages and disadvantages.
context_section_description: In interlingual machine translation systems, there are two monolingual components: the analysis of the source language and the interlingual, and the generation of the interlingua and the target language. It is however necessary to distinguish between interlingual systems using only syntactic methods (for example the systems developed in the 1970s at the universities of Grenoble and Texas) and those based on artificial intelligence (from 1987 in Japan and the research at the universities of Southern California and Carnegie Mellon). The first type of system corresponds to that outlined in Figure 1. while the other types would be approximated by the diagram in Figure 4.
  The following resources are necessary to an interlingual machine translation system:
  Dictionaries (or lexicons) for analysis and generation (specific to the domain and the languages involved).
  A conceptual lexicon (specific to the domain), which is the knowledge base about events and entities known in the domain.
  A set of projection rules (specific to the domain and the languages).
  Grammars for the analysis and generation of the languages involved.
  One of the problems of knowledge-based machine translation systems is that it becomes impossible to create databases for domains larger than very specific areas. Another is that processing these databases is very computationally expensive.
caption: Figure 4. Machine translation in a knowledge-based system.
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