Researchers at the University of Amsterdam are using neural networks to help statistical machines translate different languages. The best translation often depends on the context. Machine translation systems, such as Google Translate. How to translate a word and a phrase in the artificial translation of a large corpus. Translation tools and tools are increasingly important for people, companies, or countries in different languages.
The statistical machine translation work breaks down into short sentences and selects the words that are most likely to be translated, but does not always produce the best translations. Improved word selection systems translate into morphologically rich languages, and it is relatively easy to translate sentences into more complex language translators because they understand the grammatical function of the word in a sentence. However, it is obviously very difficult for machine translation. Because from a simpler grammar language such as the English word form does not contain enough information, it is also unable to produce the correct version of the language. The researchers said that the neural network can gain grammatical functions without explicit grammatical knowledge. This means that the method of learning the word function does not depend on carefully selected examples from researchers, which is a difficult and expensive process, especially for language translators.
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