本文摘要:Experts believe that machine translation good enough to replace advanced human translators will be widespread within five to 10 years, as language-processing technology has seen many breakthroughs in recent years, Xinhuanet.com reported on May 22.据新华网5月22日报导,由于近年来语言处置技术获得了多项突破,专家们坚信,不足以代替资深译员的机器翻译将在五至十年内普及。
Experts believe that machine translation good enough to replace advanced human translators will be widespread within five to 10 years, as language-processing technology has seen many breakthroughs in recent years, Xinhuanet.com reported on May 22.据新华网5月22日报导,由于近年来语言处置技术获得了多项突破,专家们坚信,不足以代替资深译员的机器翻译将在五至十年内普及。Zhou Ming, standing deputy dean of Microsoft Research Asia, made the statement in his keynote speech at the 2017 Global Artificial Intelligence Technology Conference, held in Beijing on May 22.5月22日,微软公司亚洲研究院常务副院长周明在于北京举办的2017全球人工智能技术大会上公开发表的主旨演说中这样说。Machine translation currently faces challenges that prevent it from reaching the standards of professional translation, Zhou noted.周明认为,当前,机器翻译面对着各种挑战,这使得其无法超过专业翻译的标准。
However, he also pointed out that several technology companies are now focusing on machine translation, and have already made great progress.不过他也认为,现在好几家技术公司正在主攻机器翻译,且已获得相当大进展。Google released its translation system in September 2016, based on recurrent neural networks.2016年9月,谷歌公司公布了自己基于迭代神经网络的翻译成系统。In addition, the artificial intelligence team at Facebook claimed to have achieved the highest accuracy yet in machine translation by using brand new neural network technology, with a translating speed nine times that of Google.此外,脸书的人工智能团队声称,通过用于新型神经网络技术,早已构建了目前为止尤为精确的机器翻译,翻译成速度为谷歌的九倍。
Apart from translation, Zhou speculated that language-processing technology, integrated with other artificial intelligence, could be applied in many fields including education, medicine and driverless cars in the near future.周明预测,除了翻译成,语言处置技术和其它人工智能,在未来还可应用于还包括教育、药物和无人驾驶在内的很多领域。
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