google translate was launched for the first time on april 2006.
when was google translate launched for the first time?
april 2006
launched in april 2006 as a statistical machine translation service, it used united nations and european parliament transcripts to gather linguistic data. rather than translating languages directly, it first translates text to english and then to the target language. during a translation, it looks for patterns in millions of documents to help decide on the best translation. its accuracy has been criticized and ridiculed on several occasions. in november 2016, google announced that google translate would switch to a neural machine translation engine - google neural machine translation (gnmt) - which translates "whole sentences at a time, rather than just piece by piece. it uses this broader context to help it figure out the most relevant translation, which it then rearranges and adjusts to be more like a human speaking with proper grammar". originally only enabled for a few languages in 2016, gnmt is gradually being used for more languages.
google translate
the google brain project contributed to google translate. in september 2016, google neural machine translation (gnmt) was launched, an end-to-end learning framework, able to learn from a large number of examples. while its introduction has increased the quality of google translate's translations for the pilot languages, it was very difficult to create such improvements for all of its 103 languages. addressing this problem, the google brain team was able to develop a multilingual gnmt system, which extended the previous one by enabling translations between multiple languages. furthermore, it allows for zero-shot translations, which are translations between two languages that the system has never explicitly seen before. google announced that google translate can now also translate without transcribing, using neural networks. this means that it is possible to translate speech in one language directly into text in another language, without first transcribing it to text. according to the researchers at google brain, this intermediate step can be avoided using neural networks. in order for the system to learn this, they exposed it to many hours of spanish audio together with the corresponding english text. the different layers of neural networks, replicating the human brain, were able to link the corresponding parts and subsequently manipulate the audio waveform until it was transformed to english text.
google brain