Traffic Analysis for Content Hosted by Google Google Switches to Its Own Translation System Google to Connect to Other IM Networks Using Jabbe.ĭecomposing the Web and Rearranging its Fragments OpenSocial, Google's APIs for Social Applications Ils peuvent ajuster leur signification culturellement appropriés d'une traduction. Et la raison en est, qu'ils peuvent ressentir les mots, et non seulement de lire et de comprendre. Mais il ne faut pas compter sur elle, comme les mots ont des significations subtiles que seuls les êtres humains peuvent détecter. Oui, une machine peut aider à atteindre plus rapidement l'homme traduction. They can adjust their meaning to a culturally appropriate translation. And the reason is, that they can feel the words, not only read and understand them. But one should not rely on it, as words have subtle meanings that only humans can detect. Yes, machine can help humans achieve a faster translation. If you are EnglishFrench bilingual, see what I mean by reading the above text translated with Google Translation System: "I do not understand! Please speak in English." In fact, I had Google translate the result back into English, and got back "Yo no entiendo! Por favor, hable en inglés." Their method would make some sense if I were, say, yelling at someone, "I don't understand you! Speak English!"įrom one (odd) point of view, that could be translated into Portuguese as "I don't understand you! Speak Portuguese!" (ie., into the speaker's native language.)īut I tried translating "I don't understand you! Speak English!" into Spanish, and got back the following: The translator took the word "português" to mean "my native language." Since the native language of the original text was Portuguese, the machine translated that into "English" - the native language of the translated text. If I translate "Estou aprendendo português" from Portuguese to English I get this translation "I am learning English".! The switch is a sign that Google's system has improved a lot and could soon be ready for expanding its coverage. You can compare the new Google Translate with Babel Fish, a site that uses Systran to provide translations. We then apply statistical learning techniques to build a translation model," explains Franz Och. Several research systems, including ours, take a different approach: we feed the computer with billions of words of text, both monolingual text in the target language, and aligned text consisting of examples of human translations between the languages. "Most state-of-the-art commercial machine translation systems in use today have been developed using a rules-based approach and require a lot of work by linguists to define vocabularies and grammars. Until now, Google used its own system only for Arabic, Chinese, and Russian. Google switched the translation system from Systran to its own machine translation system for all the 25 language pairs available on the site.
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