2017年1月7日《经济学人》封面文章学习资料

20170107TE COVERY译言网翻译文本

Now we’re talking

Voice technology is making computers less daunting and more accessible

语音技术 轻而易“语”

有了语音技术，电脑不再令人敬而远之，反而更加平易近人

Any sufficiently advanced technology, noted Arthur C Clarke, a British science-fiction writer, is indistinguishable from magic. The fast-emerging technology of voice computing proves his point. Using it is just like casting a spell: say a few words into the air, and a nearby device can grant your wish.

英国科幻小说作家亚瑟·克拉克（Arthur C. Clarke）曾经指出，任何科技只要先进到足够的程度，就和魔法没有区别。迅速兴起的语音电脑证明了他的观点。它用起来就像是变魔法：对着空气说句话，附近的智能设备就会帮你如愿以偿。

The Amazon Echo, a voice-driven cylindrical computer that sits on a table top and answers to the name Alexa, can call up music tracks and radio stations, tell joke, answer trivia questions and control smart appliances; even before Christmas it was already resident in about 4% of American households. Voice assistants are proliferating in smart phones, too: Apple's Siri handles over 2bn commands a week, and 20% of Google searches on Android- powered handsets in America are input by voice. Dictating e-mails

and text messages now works reliably enough to be useful. Why type when you can talk?

亚马逊智能音箱（Amazon Echo）是一种声控筒状台式电脑，听到“阿丽夏”（Alexa）这个名字，它就会做出反应，挑选歌曲，选择电台，讲笑话，回答各种琐碎问题，还能控制智能设备；甚至早在圣诞节到来之前，它就已经入住了4%的美国家庭。语音智能助手还扩张到了智能手机行业：苹果（Apple）的语音助手西里（Siri）每周要处理超过20亿个指令；在美国，安卓手机的谷歌搜索指令有20%都是通过语音发布的。电邮和短信的语音输入技术已经发展得足够稳定，十分好用了。说话就能解决，何必还去打字？

This is a huge shift. Simple though it may seem, voice has the power to transform computing, by providing a natural means of interaction. Windows, icons and menus, and then touchscreens, were welcomed as more intuitive ways to deal with computers than entering complex keyboard commands. But being able to talk to computers abolishes the need for the abstraction of a“user interface” at all. Just as mobile phones were more than existing phones without wires, and cars were more than carriages without horses, so computers without screens and keyboards have the potential to be more useful, powerful and ubiquitous than people can imagine today.

这种转变非同小可。尽管语音技术看起如此简单，但通过提供自然的交流方式，它具备着改变电脑的力量。从Windows操作系统，到图标和菜单，再到触屏技术，这些和电脑打交道的方式更加直观，比输入复杂键盘指令更受欢迎。但是，一旦能够与电脑交谈，就不存在将“用户界面”抽象出来的必要了。就像手机不光是没有线的电话，汽车不光是没有马的马车，没有屏幕和键盘的电脑也有潜力变得更好用、更强大、更无所不在，超乎今人的想象。

Voice will not wholly replace other forms of input and output. Sometimes it will remain more convenient to converse with a machine by typing rather than talking (Amazon is said to be working on an Echo device with a built-in screen).But voice is destined to account for a growing share of people's interactions with the technology around them, from washing machines that tell you how much of the cycle they have left to virtual assistants in corporate call-centres. However, to reach its full potential, the technology requires further breakthroughs-and a resolution of the tricky questions it raises around the trade-off between convenience and privacy.

语音技术并不会完全替代其他形式的输入与输出。有时候，要和机器聊天，打字仍旧比语音更容易（据说，亚马逊打算研发一种带有内置屏幕的语音设备）。不过，从告诉你剩余洗衣时间还有多长的洗衣机，到企业呼叫中心的虚拟助手，作为人们与周边科技互动的方式，语音注定会越来越受青睐。然而，要充分发挥其潜力，语音技术还需要进一步突破，解决好由此产生的微妙问题，拿捏好便利性与否与隐私权之间的平衡。

Alexa, what is deep learning? Computer-dictation systems have been around for years. But they were unreliable and required lengthy training to learn a specific user's voice. Computers' new ability to recognise almost anyone's speech dependably without training is the latest manifestation of the power of \which a software system is trained using millions of examples,

usually culled from the internet. Thanks to deep learning, machines now nearly equal humans in transcription accuracy, computerised translation systems are improving rapidly and text-to-speech systems are becoming less robotic and more natural-sounding. Computers are, in short, getting much better at handling natural language in all its forms (see Technology Quarterly).

阿丽夏，深度学习是啥？

电脑指令(口述)系统已经伴随我们好些年了。但是，他们性能不稳定，需要经过长时间训练，才能识别特定用户的语音。“无需训练就能可靠地识别几乎任何人的讲话，这是电脑的新功能，也是“深度学习”能力的最新印证。深度学习”是一种人工智能技术，该技术可让某种软件系统接收上百万次案例训练，这些案例往往是从网络上精选出来的。现在，有了深度学习技术，机器在转录准确性上，已经与人无异，电脑翻译系统正在飞速发展，文本转语音系统的机器人腔越来越少，更加接近自然人声。简言之，电脑对各种自然语言的处理能力都今非昔比了。

Although deep learning means that machines can recognise speech more reliably and talk in a less stilted manner, they still don't understand the meaning of language. That is the most difficult aspect of the problem and, if voice-driven computing is truly to flourish, one that must be overcome. Computers must be able to understand context in order to maintain a coherent conversation about something, rather than just responding to simple, one-off voice commands, as they mostly do today(“Hey, Siri, set a timer for ten minutes”).Researchers in universities and at companies large and small are working on this very problem, building \” that can hold more elaborate conversations about more complex tasks, from