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These days searching for a number【C1】______ telephone directory seems very o
These days searching for a number【C1】______ telephone directory seems very o
游客
2023-12-22
12
管理
问题
These days searching for a number【C1】______ telephone directory seems very old-fashioned. Voice recognition systems are becoming more and more【C2】______: the best of them apparently recognise 49【C3】______.
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,【C4】______ which now uses a voice recognition system. I told the machine I wanted the number for "Harlem Auto Mall" and she—for【C5】______—replied "Harlem Public School 154". No doubt like lots of people, I【C6】______.
Machines, you see, have personalities, and hanks, phone companies, railways and 【C7】______ 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【C8】______—Room 325 in McClatchy Hall—in Stanford University in California. It’s the site of the drily-entitled but fascinating laboratory for " 【C9】______", and the domain of a genial, enthusiastic professor called Clifford Nass who studies, quite simply, how people and machines get on, particularly when【C10】______.
In his lab, a stream of students and local people of all shapes and sizes undergo tests.【C11】______ 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【C12】______ than by male ones. On the upside, male voiced machines are perceived to【C13】______. 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【C14】______.
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. She tells me, say, to【C15】______ and—I fancy, at least—gets exasperated if I don’t follow her directions: "Recalculating Route", she snaps,【C16】______.
Now, in Germany when they tried a similar system, men reacted against being given directions by a female voice so it had to【C17】______. Old people, by the way, take advice more readily from young people than from people of their own age.
【C18】______. Professor Nass is working on a system where the machine-voice changes according to how you address it. He’s discovered that irritable drivers can calm down if 【C19】______ is subdued—though, for some reason that he doesn’t quite understand, calm drivers get wound up by subdued, low-key voices that don’t vary in pitch. So the next task is to vary the system’s voice according to how grumpy you, the driver, are. If you sound【C20】______, the machine will change tone to calm you down. [br] 【C17】
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 recognize 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 helplines 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 Interactive 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. On the upside, 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. 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.
Now, in Germany when they tried a similar system, men reacted against being given directions by a female voice so it had to be taken off the market. Old people, by the way, take advice more readily from young people than from people of their own age.
Tone matters to drivers. Professor Nass is working on a system where the machine-voice changes according to how you address it. He’s discovered that irritable drivers can calm down if the voice on the navigation system is subdued—though, for some reason that he doesn’t quite understand, calm drivers get wound up by subdued, low-key voices that don’t vary in pitch. So the next task is to vary the system’s voice according to how grumpy you, the driver, are. If you sound aggressive to the machine, the machine will change tone to calm you down.
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答案
be taken off the market
解析
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