Based on our record, Microsoft Translator should be more popular than Apertium. It has been mentiond 8 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.
Do you have access to Microsoft products? They have an appthat students can add to a device that will translate your spoken words into text (you have to have the app or website open as well). There are several other Microsoft translation tools that would also work in different ways, which you may be able to use without a Microsoft license. Google’s translation tools are not as well integrated. Source: over 1 year ago
Translator.microsoft.com works fine in a web browser - and all I have gotten is positive feedback from my colleagues in UA about the quality/accuracy of the translations. Source: over 1 year ago
Iirc Microsoft, Apple, and Google are working on this with the help of AI. We are playing around with the Microsoft Neural Machine Translator at work to assist with translation for non-English speaking patients. https://translator.microsoft.com. Source: over 1 year ago
It is very interesting to understand how Machine Translation engines work such as Masakhane translate, Google translate, Amazon, Microsoft Translator, etc. - Source: dev.to / almost 2 years ago
For anyone who does not know the language and is looking for an effective way to bridge the language gap: I have been using https://translator.microsoft.com/ and it has been very useful. Source: about 2 years ago
This is very cool, looking forward to it! I've been doing the same thing with Spanish Wikipedia articles for a while, using a few lines of Bash + Regex. I was using Apertium for it. https://apertium.org/ It's definitely worse than most ML-based solutions, but it works reliably and fast; you can run it entirely offline. With Spanish translations, the main problem I was facing is lack of vocabulary, so I created - Source: Hacker News / 9 months ago
I used to keep track of the state of machine translation some years back. I think the way you measure the success of an automated translation is edit distance, i.e. How many manual edits you need to make to a translated text before you reach some acceptable state. I suppose it's somewhat subjective, but it is possible to construct a benchmark and allow for multiple correct results. The best resources I knew back... - Source: Hacker News / almost 2 years ago
Apertium is one of them. We make open-source rule-based machine translation systems, and our core tools are in C++. A few of our proposed ideas involve modifying those C++ tools with new features or improvements to existing features. Source: about 3 years ago
Google Translate - Google's free service instantly translates words, phrases, and web pages between English and over 100 other languages.
DeepL Translator - DeepL Translator is a machine translator that currently supports 42 language combinations.
Mate Translate - Ultimate translation app for Mac, iOS, Chrome and many more
Yandex.Translate - Yandex.Translate is an online dictionary and translation solution.
Crowdin - Localize your product in a seamless way
Crow Translate - A simple and lightweight translator that allows to translate and speak text using Google, Yandex and Bing.