The main types of modern machine text translation are Statistical Machine Translation (SMT) and Rule-Based Machine Translation (RBMT).


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Basic pronciples of how Google Translate works

Google Translate

Google Translate uses SMT. A feature of Google Translate is the translation method: it is not based on the analysis of grammar rules, but is based on finding language matches between the translated text and a giant array of the service, which consists of words entered by the user earlier during their translation. These blocks of text are compiled from all possible reliable sources. An example is the documents of state organizations. They are some of the most trusted sources for the database. The advantage is that such documents contain information that is available in many languages, like in this tool

Books are also important for the development of Google Translate. At the moment, it is known that the "corpus" of Google Translate has more than a trillion words. Thus, the service actively uses custom unique translation to improve the quality characteristics of machine text translation by entering custom phrase variants into the database. Thus, this combination contributes to an increase in the quality level of generating a unique text.


Statistical modern translation requires analysis of parallel language pairs in order to generate text. He independently adjusts to new vocabulary. The system independently enters into its perfect database new variations of the translation of words or phrases, if they differ. She keeps in memory new versions of possible translations and can use these versions in the future. One of the main advantages of SMT is that it is updated and developed in parallel with the language. That is, if a new word appears or its lexical meaning changes, the system recognizes this and updates its database. And, as a consequence, the "training" of the system is accelerated and the quality of text generation is improved - read more here Wiki.


But there is also a significant disadvantage to SMT. This system requires high-performance hardware. A huge amount of computation is required to improve the program. Also, SMT translation is characterized by the fact that the quality of text generation depends entirely on the amount of data in the service corpus. Variations of text translation generated by the service more often meet the expectations of a modern person. Although it is difficult to predict in advance the textual content that Google Translate will generate.