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Voice Recognition Becomes More Intelligent

These days searching for a number in a five centimetre thick telephone directory seems very old fashioned. Voice recognition systems are becoming more and more common and efficient: the best of them apparently recognise 49 out of every 50 words.

These devices save companies a huge amount of money. Stephen Evans in New York has been talking to the machines and to the men who design them.

I had a bit of a Basil Fawlty moment, the other day. I rang 411, the American directory enquiries which now uses a voice recognition system. I told the machine I wanted the number for "Harlem Auto Mall" and she -- for this machine had a female voice -- replied "Harlem Public School 154". No doubt like lots of people, I found myself ranting.

Machines, you see, have personalities, and banks, phone companies, railways and all kinds of alleged help-lines are spending a lot of money trying to find out what kinds of voices to give the machines that speak to us, the public, on their behalf.

Much of the research is conducted in a small room -- Room 325 in McClatchy Hall -- in Stanford University in California. It's the site of the drily-entitled but fascinating laboratory for "Communication between Humans and Inter-active Media", and the domain of a genial, enthusiastic professor called Clifford Nass who studies, quite simply, how people and machines get on, particularly when the machines talk to the people.

In his lab, a stream of students and local people of all shapes and sizes undergo tests. Voices of different ages and accents are played to them and their reactions noted: "Did you trust that voice?" "Did this one have authority?"

Generally, the tests show that people are less persuaded by female voices than by male ones (though people are more likely to be antagonised by a male voice). On the up side, male voiced machines are perceived to have energy and authority. One of the results of that, for example is that in Japan a stock-broking company used a female voice on its machine to give information on stocks and shares but then a male one to make the actual sale.

Now, in many parts of the world, when you hire a car, you get a navigation system -- a little electronic map on a screen with a machine voice. In America, it's a female voice (whom I like to call Gladys). She tells me, say, to make a right in two miles and -- I fancy, at least -- gets exasperated if I don't follow her directions: "Recalculating Route", she snaps, in her American English.

译文：

语音识别系统智能化程度更高

近来，在一本五厘米厚的电话簿里寻找电话号码似乎已经非常过时了。语音识别系统变得越来越常见、高效：其中最好的系统可以从每五十个单词里清楚地辨识出四十九个。

这些设备省去了公司一大笔钱。纽约的斯蒂芬·埃文斯一直在同这些机器及其设计者们进行交谈。

前几天我心情有些不爽。那天我拨打了号码411，这是美国电话查询体系，现在使用的是语音识别系统。我告诉机器我需要“哈莱姆汽车基地”的号码，她（因为这部机器发出的是女声）回答道“哈莱姆公立学校154”。毫无疑问，同很多人一样我发现我开始咆哮了。

正如大家所看到的那样，这些机器都具有人的特性，而银行、电话公司、铁路系统以及各种所谓的帮助热线正在投下大笔的金钱，试图找出将各种声音输入到代表他们跟我们说话的机器里。

大部分研究工作都在加州斯坦福大学的一间小房间——麦克克莱契大厅325室进行。这个场所有个干巴巴的称号——“人机对话”实验室，但它却是一家令人神往的实验室，同时也是一位亲切而富有激情的教授的领地。他叫克利福德·纳斯，其研究内容很简单，就是研究人与机器怎样相处，特别是当机器同人们交谈时怎样进行相处。

在他的实验室里，有一群学生和形象各异的当地人在进行实验。向这些人播放着由不同年龄和口音发出的声音，并对他们的反应做好如下记录：“你信任这个声音吗？”或者“这个声音有权威性吗？”

一般而言，实验显示男性声音比女性声音更具有说服力（尽管男性声音更容易招致敌对）。此外人们认为男性发音的机器具有力量和权威性。这些结论实际运用的一个实例就是日本的股票经纪公司使用女性声音机器来提供股票和股份信息，而进行实际销售时则使用男性声音机器。

目前在世界的许多地方，你在租用汽车时都会获得一个导航系统，它是显示在屏幕上的一张小型电子地图，可以发出机器声音。在美国，这是一个女性声音（我喜欢将她叫做格拉迪斯）。比如她会告诉我在两公里的地方向右转，而如果我没有遵从她的指示，她就会发怒（至少我是这么认为的）：“重新计算路线”，她用美式英语厉声说道。