神奇的機器翻譯系統(tǒng)

山東 孫啟祿

臉書開發(fā)了首個機器學(xué)習(xí)模型， 它可以實現(xiàn)100種語言中的任意兩種語言之間的翻譯，而不需要先轉(zhuǎn)換成英語，并且臉書還在不斷地完善這個模型。

難詞探意

1. multilingual /,m?lti'l??ɡw?l/ adj. 說（或用）多種語言的

2. intermediate /,?nt?'mi?di?t/ adj. 中間的；中等的

Facebook has developed the first machine learning model that can translate between any two of 100 languages without going into English first. It says the new multilingual machine translation model was created to help its more than two billion users worldwide. The company is still testing the translation system,which it calls M2M-100 and hopes to add to different products in the future.

Angela Fan, a research assistant at Facebook, said the model produces better results than any other machine learning systems that depend on English to help in the translation process. The other systems use it as an intermediate step—like a bridge—to translate between two non-English languages.

One example would be a translation from Chinese to French. Fan noted that many machine translation models begin by translating from Chinese to English first, and then from English to French. This is done “because English training data is the most widely available,” she said. But such a method can lead to mistakes in translation.

Facebook says about two-thirds of its users communicate in a language other than English. The company already carries out an average of 20 billion translations every day on Facebook's News Feed.But it faces a huge test with many users publishing large amounts of content in more than 160 languages.

One difficulty the team faced was trying to develop an effective machine translation system for language combinations that are not widely used. Facebook calls these “l(fā)ow-resource languages”. The data used to create the new model was collected from content available on the Internet. But there is limited Internet data on low-resource languages.

For now, it plans to continue exploring new language research methods while working to improve the new model. No date has been set for launching the translation system on Facebook.

But Angela Fan said the new system marks an important step for Facebook, especially for the times we live in. “Breaking language barriers through machine language translation is one of the most important ways to bring people together, provide accurate information on COVID-19, and keep them safe from harmful content,” she said.

1. What can we know about M2M-100 from the first paragraph?

A. It is still in the testing stage at present.

B. It can translate any of the world languages.

C. It is the first translation system in the world.

D. It has been widely used by two billion users.

2. What does the underlined word “it” in Para. 2 most probably refer to?A. The model. B. The machine.

C. English. D. A non-English language.

3. What are “l(fā)ow-resource languages”?

A. Languages that are used worldwide. B. Languages that are not widely used.

C. Languages that have data on the Internet. D. Languages that Facebook uses in its system.

4. What is Angela Fan's attitude towards the new system?

A. Doubtful. B. Negative. C. Positive. D. Objective.

Choose one word from the words given below in proper forms to complete the sentences.

1. The sudden change of the climate has drawn ___________attention to the benefit of green energy.

2. He was occupied with a ___________of an English novel written by Jane Austen last week.

3. We live in an age when more information is ___________with greater ease than ever before.

4.The key to successful small talk is learning how to connect with others,not just ________with them.

5. The reason why people carry umbrellas in hot weather is that the hot sun may be ___________to the exposed skin.