Machine translation is also scalable across different languages
Posted: Sat Feb 08, 2025 7:15 am
This leads to another advantage of raw MT, which is that it’s endlessly scalable. For one, the length of the text is not an issue with machine translation. This is unlike human translation, where the longer the text, the longer the turnaround time due to the limits of human ability to read, translate, and write.
MT systems can handle many different languages, some even reaching over a hundred. It’s just a matter of choosing the right systems for the job, and your text can be made available in many different languages.
Because of this, machine translation shines when used in oman mobile database automatic workflows, particularly those involving multiple languages. Think, for example, text on ecommerce websites. Having an option to translate your webpages will make them more accessible to consumers, which means they are more likely to make a purchase. This is what happened in the case of eBay, where machine translation helped increase sales by over 10%.
Another good example is the case of AirBnB. AirBnB is an app that caters to travelers from all around the world who are looking for lodging. And there is often a linguistic gap that exists between the “hosts” and “guests” who use the app.
Before AirBnB integrated machine translation into their app, hosts would have to create the same listing in different languages, often with the help of Google Translate or some other external MT engine.
What AirBnB did was build a proprietary MT engine that seamlessly detects a user’s preferred language and automatically translates text into that language. This way, hosts no longer need to create multiple versions of the same listing in different languages.
MT systems can handle many different languages, some even reaching over a hundred. It’s just a matter of choosing the right systems for the job, and your text can be made available in many different languages.
Because of this, machine translation shines when used in oman mobile database automatic workflows, particularly those involving multiple languages. Think, for example, text on ecommerce websites. Having an option to translate your webpages will make them more accessible to consumers, which means they are more likely to make a purchase. This is what happened in the case of eBay, where machine translation helped increase sales by over 10%.
Another good example is the case of AirBnB. AirBnB is an app that caters to travelers from all around the world who are looking for lodging. And there is often a linguistic gap that exists between the “hosts” and “guests” who use the app.
Before AirBnB integrated machine translation into their app, hosts would have to create the same listing in different languages, often with the help of Google Translate or some other external MT engine.
What AirBnB did was build a proprietary MT engine that seamlessly detects a user’s preferred language and automatically translates text into that language. This way, hosts no longer need to create multiple versions of the same listing in different languages.