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History of machine translation. Machine translation is a sub-field of computational linguistics that investigates the use of software to translate text or speech from one natural language to another. In the 1950s, machine translation became a reality in research, although references to the subject can be found as early as the 17th century.
It has Arabic to English translations and English to Arabic, as well as a significant quantity of technical terminology. It is useful to translators as its search results are given in context. Almaany offers correspondent meanings for Arabic terms with semantically similar words and is widely used in Arabic language research.
Google Translate is a multilingual neural machine translation service developed by Google to translate text, documents and websites from one language into another. It offers a website interface, a mobile app for Android and iOS, as well as an API that helps developers build browser extensions and software applications.
Machine code is generally different from bytecode (also known as p-code), which is either executed by an interpreter or itself compiled into machine code for faster (direct) execution. An exception is when a processor is designed to use a particular bytecode directly as its machine code, such as is the case with Java processors.
Interlingual machine translation. 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 ...
Machine translation used a method based on dictionary entries, which means that the words were translated as they are by a dictionary. Statistical [ edit ] Statistical machine translation tried to generate translations using statistical methods based on bilingual text corpora, such as the Canadian Hansard corpus, the English-French record of ...
There are three different types of rule-based machine translation systems: Direct Systems ( Dictionary Based Machine Translation) map input to output with basic rules. Transfer RBMT Systems ( Transfer Based Machine Translation) employ morphological and syntactical analysis. Interlingual RBMT Systems ( Interlingua) use an abstract meaning.
Dictionary-based machine translation. Machine translation can use a method based on dictionary entries, which means that the words will be translated as a dictionary does – word by word, usually without much correlation of meaning between them. Dictionary lookups may be done with or without morphological analysis or lemmatisation.