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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 . [ 3 ]
Speech translation: Microsoft Translator is integrated into Microsoft Speech services which is an end-to-end REST based API that can be used to build applications, tools, or any solution requiring multi-languages speech translation. Speech to speech translation is available to or from any of the conversation languages, and speech to text ...
Free, commercial (varies by plan) 3.0: No: 50+ Both rule-based and statistical models developed by IBM Research. Neural machine translation models available through the Watson Language Translator API for developers. [4] [5] Microsoft Translator: Cross-platform (web application) SaaS: No fee required: Final: No: 100+ Statistical and neural ...
Google Translate's NMT system uses a large artificial neural network capable of deep learning. [1] [2] [3] By using millions of examples, GNMT improves the quality of translation, [2] using broader context to deduce the most relevant translation.
In addition to machine translation, there is also an accessible and complete English-Russian and Russian-English dictionary. [6] There is an app for devices based on the iOS software, [7] Windows Phone and Android. You can listen to the pronunciation of the translation and the original text using a text to speech converter built in.
Text-to-Speech may be used by apps such as Google Play Books for reading books aloud, Google Translate for reading aloud translations for the pronunciation of words, Google TalkBack, and other spoken feedback accessibility-based applications, as well as by third-party apps. Users must install voice data for each language.
Machine translation, like DeepL or Google Translate, is a useful starting point for translations, but translators must revise errors as necessary and confirm that the translation is accurate, rather than simply copy-pasting machine-translated text into the English Wikipedia. Do not translate text that appears unreliable or low-quality.
With its widespread use in social media such as blogs, Facebook and X (formerly Twitter), the analysis of Hinglish using computers has become important in a number of natural language processing applications like machine translation (MT) and speech-to-speech translation. [31] [32]
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