Machine translation is democratizing science
Posted: Sat Feb 08, 2025 7:15 am
With recent updates, all that trouble is no longer necessary. Hosts can just create a listing in their own language, and let AirBnB’s Translation Engine do the rest.
In fact, users don’t even have to click a button anymore to translate—the app automatically detects the user’s preferred language and translates listings, reviews, and messages accordingly.
And because it’s specially trained, the quality of the translated text is definitely better than what could be achieved with generic machine translation systems.
Parting thoughts
AirBnB’s Translation Engine is a very good example of a oman mobile database machine translation workflow that is well-thought out from end to end. It plays to the company’s strength, which is the availability of a vast corpus of multilingual data, in order to improve the quality of translations in its specific domain. These gains are then immediately brought to the app’s users through seamless UX design. This is something that other businesses can learn from when deciding on how to leverage machine translation in their own operations.
A recent article on ScienceDaily discussed how machine translation could make English-only science accessible to all researchers and readers around the world.
Students and scientists at UC Berkeley, have said of the currently available machine translation systems that “though flawed, they have become good enough for researchers to broadly translate their work into other languages”.
This is a most welcome observation that shows proof of the increased quality of machine translation in recent years.
In fact, users don’t even have to click a button anymore to translate—the app automatically detects the user’s preferred language and translates listings, reviews, and messages accordingly.
And because it’s specially trained, the quality of the translated text is definitely better than what could be achieved with generic machine translation systems.
Parting thoughts
AirBnB’s Translation Engine is a very good example of a oman mobile database machine translation workflow that is well-thought out from end to end. It plays to the company’s strength, which is the availability of a vast corpus of multilingual data, in order to improve the quality of translations in its specific domain. These gains are then immediately brought to the app’s users through seamless UX design. This is something that other businesses can learn from when deciding on how to leverage machine translation in their own operations.
A recent article on ScienceDaily discussed how machine translation could make English-only science accessible to all researchers and readers around the world.
Students and scientists at UC Berkeley, have said of the currently available machine translation systems that “though flawed, they have become good enough for researchers to broadly translate their work into other languages”.
This is a most welcome observation that shows proof of the increased quality of machine translation in recent years.