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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]
This template creates an external link to a Google Translate page, which can translate the text from a Web page in a source language to a destination language. Syntax: {{Google translation|destination language code|source language code|URL of page to translate|link text}}
Weblate is an open source web-based translation tool with version control. It includes several hundred languages with basic definitions, and enables the addition of more language definitions, all definitions can be edited by the web community or a defined set of people, as well as through integrating machine translation, such as DeepL, Amazon Translate, or Google Translate.
Google Translate previously first translated the source language into English and then translated the English into the target language rather than translating directly from one language to another. [11] A July 2019 study in Annals of Internal Medicine found that "Google Translate is a viable, accurate tool for translating non–English-language ...
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 ...
View a machine-translated version of the Japanese article. 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.
The APIs provide functionality like analytics, machine learning as a service (the Prediction API) or access to user data (when permission to read the data is given). Another important example is an embedded Google map on a website, which can be achieved using the Static Maps API, [1] Places API [2] or Google Earth API. [3]
Users could then review and improve the automatic translation by clicking on the sentence and fixing a translation, or using Google's translation tools to help them translate by clicking the "Show toolkit" button. Users could view translations previously entered by other users in the "Translation search results" tab or use the "Dictionary" tab ...