Some of you may have noticed that according to the first graphic, Yandex is supposed to be faster than Google whereas the following benchmarks always show Yandex to be slower. Another significant factor when it comes to translator performance is the size of the payload. So, we’ve analyzed the providers’ performance depending on different language pairs. It should be noted that Yandex is very consistent and offers almost identical response times for any language pair even for English to Chinese where Bing and Google takes significantly longer.īenchmark #4: Performance depending on the size of the translation request It clearly shows the use of a pivot language here, as sometimes, a provider cannot translate directly from one language to another, so what they do, is translate into an other language first from which they can translate to the requested target language.Īs expected it takes much more time to process the translation. The graphic curves of Bing and Google results look alike except for the English to Hindu pair where Google’s response time peaks.Bing is still the fastest performer and is only beaten once by Google for English to German translations.Results here do not include DeepL which does not support Chinese or Arabic (at the time this article was written). This time, we run a benchmark with English as the source language and Spanish, Chinese (Mandarin), Arabic, Russian, Hindi, Portuguese, French and German (not technically one of the most spoken language but quite used in Europe) as the target languages. Moving on, we realized that not everybody speaks French (shocking news I know) so what about the most spoken languages in the world? Yandex and Google are respectively ranked 2nd and 3rd with a response time of 355 and 418 ms.īenchmark #2: The most spoken language pairs.
Now that you know everything about the Translation providers we use at Weglot, let’s dive into our benchmark!įor our first run, we wanted to keep it simple. Our Translation providers Performance Benchmark It uses convolutional neural networks built on the Linguee database. DeepLĭeepL is the most recent provider, launched in 2017 by Linguee and it supports 9 languages. The Google Translate service was launched in April 2006, and their neural translation service in November 2016. The service now supports more than 60 languages. In November 2016, they introduced translation using deep neural networks for nine of its highest traffic languages.
#Etienne trainslation software#
The first version of the Bing Microsoft Translator software was released between 19. Here are the services we will compare today. Weglot uses four different translation providers to cover all the language pairs that we support. The average response time is computed out of 100 requests. In order to ensure accurate results and fairness between the different third parties, we wrote a script that measures average response time under the same environment for each translation provider services, meaning that we would use the same language pair (obviously) and the same dictionary. Today, you can already find various articles and benchmarks online about the translation quality of those providers but not so much about performance, so let’s crunch numbers!
So the APIs performance is an everyday priority for us.Īs the quality of our service relies on those third parties applications for machine translation, it’s quite important for us to know the strengths and weaknesses of each of them. To provide those translations, we rely on several Translation providers and we send tens of thousands of API requests to those Translation providers on a daily basis. It’s a great way for them to not start their translation work from scratch and to save a lot of time. At Weglot, one of our main features is to supply our customers with a first automatic translation layer when they have new content to translate.
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