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Welcome to the machine

Marzo 2017
Traduttori automatici: segneranno la fine dell’apprendimento delle lingue? E soprattutto delle lingue imparate in classe? Assolutamente no. Sono un valido aiuto, ma nessuna macchina potrà mai sostituirsi alla figura umana...

di Bryan Lynn | Voice Of America

File audio:

Speaker: Rachel Roberts (Standard British accent)

Some machines can take something written in one language and give users the same or similar wording in another language. These machines are designed to do this kind of work quickly and without mistakes. The quality of translation software programmes has greatly improved in recent years. People use machine translators for day-to-day activities, while others use it in their job. But how will this affect language learning across the world? Will fewer people decide to take traditional language classes?


One of the most widely used machine translation services is Google Translate. Google says the service completes billions of translation requests, involving 103 languages, each year.
Sundar Pichai is Google’s Chief Executive Officer. He told a recent launch event that the company has made important progress with machine translation in the past few years. He said Google had previously used a system that translated on what he called a phrase-by-phrase level. This system created speech that could usually be understood, but did not sound natural.
The new system is known as neural machine translation and, rather than working at a phrase level, it takes entire sentences. It uses large amounts of computer information to learn over time how to produce translations that sound more like real human language.


Other companies and organizations are also studying neural machine translation. It is closely related to a machine learning method known as deep learning.
Deep learning involves putting large amounts of data into a computer for processing. The computer then uses an algorithm to learn how to recognize and organize different objects, including words and sentences.


Philipp Koehn teaches at Johns Hopkins University in Baltimore, Maryland. He has studied machine translation for many years. Koehn agrees that the quality of machine translation has improved a lot, but he says machines still have a long way to go to catch up with humans: “I would be very cautious about any claims about near human-level quality. There are just too many problems.” Koehn helped to create an open source machine translation system called Moses. Facebook, Amazon and other big companies now use this service. Koehn does not think the wide availability and future improvements in software will lead people to stop studying languages.

The cultural aspect

Marty Abbott agrees. She is the executive director of the American Council on the Teaching of Foreign Languages. Abbott says teachers can act as a bridge for students to learn about new cultures – something technology cannot provide. And you need to understand a culture if you want to translate effectively.  
Abbott says many young people want to try to learn one or more foreign languages to connect with people around the world. Some might start out using Google Translate, but then decide they want to expand their learning and knowledge in the classroom.

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