Based on our record, WordNet should be more popular than Microsoft Translator. It has been mentiond 28 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.
TL;DR: The authors pretrain the model to classify images into Wordnet synsets[a] that appear in the caption, using a standard Cross Entropy loss. They keep the number of classes relatively small by removing any synsets that don't show up in captions at least 500 times in the dataset. It seems to work well. My immediate question is: Why not classify among the entire hierarchy of all Wordnet synsets? --- [a]... - Source: Hacker News / 25 days ago
To operationalize this intuition, the Microsoft and UC Berkeley researchers use WordNet and Wiktionary to augment the text in image-text pairs. The concept itself is augmented for isolated concepts, such as the class labels in ImageNet, whereas for captions (such as from GCC), the least common noun phrase is augmented. Equipped with this additional structured knowledge, contrastively pretrained models exhibit... - Source: dev.to / 2 months ago
If you like this, definitely check out WordNet (https://wordnet.princeton.edu/). - Source: Hacker News / 5 months ago
I didn't understand well what you meant, but maybe this site can help you: https://wordnet.princeton.edu/. Source: over 1 year ago
What I'd do is work with a huge database like WordNet and then try to "extrapolate" BIP39 to 4096 words by creating queries against WordNet to obtain words meeting the constraints you'd like to keep. Source: over 1 year ago
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 / about 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
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Artha - Artha is a handy thesaurus based on WordNet with distinct features like global hotkey look-up...
DeepL Translator - DeepL Translator is a machine translator that currently supports 42 language combinations.
WordWeb - One-click lookup in any almost any Windows program; Hundreds of thousands of definitions and synonyms; The latest international English words; Works offline, or reference to Wikipedia and web references.
Mate Translate - Ultimate translation app for Mac, iOS, Chrome and many more