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Google Translate is not as reliable as human translation. When text is well-structured, written using formal language, with simple sentences, relating to formal topics for which training data is ample, it often produces conversions similar to human translations between English and a number of high-resource languages.
Reverso is a French company specialized in AI-based language tools, translation aids, and language services. [2] These include online translation based on neural machine translation (NMT), contextual dictionaries, online bilingual concordances, grammar and spell checking and conjugation tools.
Linguee is an online bilingual concordance that provides an online dictionary for a number of language pairs, including many bilingual sentence pairs. As a translation aid, Linguee differs from machine translation services like Babel Fish, and is more similar in function to a translation memory.
If a homonym is detected in a sentence to be translated, the translator presents various interpretations for a homograph found in an input sentence. Users can choose a specific meaning and receive the retranslated sentence associated with their selected sense. Each sense is represented as a clear image on the translation result screen. [5]
The following table compares the number of languages which the following machine translation programs can translate between. (Moses and Moses for Mere Mortals allow you to train translation models for any language pair, though collections of translated texts (parallel corpus) need to be provided by the user.
The reception of DeepL Translator has been generally positive. TechCrunch appreciates it for the accuracy of its translations and stating that it was more accurate and nuanced than Google Translate. [3] Le Monde thank its developers for translating French text into more "French-sounding" expressions. [38]
Machine translation is use of computational techniques to translate text or speech from one language to another, including the contextual, idiomatic and pragmatic nuances of both languages. Early approaches were mostly rule-based or statistical. These methods have since been superseded by neural machine translation [1] and large language models ...
As the translation systems are not able to store all native strings and their translations, a document is typically translated sentence by sentence. Language models are typically approximated by smoothed n -gram models , and similar approaches have been applied to translation models, but this introduces additional complexity due to different ...
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