剑桥雅思13Test1阅读passage3真题+翻译(2)
2023-06-08 15:46:15 来源:中国教育在线
剑桥雅思13Test1阅读passage3真题+翻译(2) 关于这个问题下面小编就来为各个考生解答下。
剑桥雅思13Test1阅读passage3真题+翻译
READING PASSAGE 3
You should spend about 20 minutes on Questions 27-40, which are based on Reading Passage 3 below.
Artificial artists
人工智能艺术家
Can computers really create works of art?
电脑真的能创作艺术吗?
Researchers like Colton don't believe it is right to measure machine creativity directly to that of humans who ‘have had millennia to develop our skills’. Others, though, are fascinated by the prospect that a computer might create something as original and subtle as our best artists. So far, only one has come close. Composer David Cope invented a program called Experiments in Musical Intelligence, or EMI. Not only did EMI create compositions in Cope’s style, but also that of the most revered classical composers, including Bach, Chopin and Mozart. Audiences were moved to tears, and EMI even fooled classical music experts into thinking they were hearing genuine Bach. Not everyone was impressed however. Some, such as Wiggins, have blasted Cope's work as pseudoscience, and condemned him for his deliberately vague explanation of how the software worked. Meanwhile, Douglas Hofstadter of Indiana University said EMI created replicas which still rely completely on the original artist’s creative impulses. When audiences found out the truth they were often outraged with Cope, and one music lover even tried to punch him. Amid such controversy, Cope destroyed EMI's vital databases.
像Colton这样的研究者并不认为我们应当直接用人类艺术的标准来衡量机器创作,毕竟人类“有着数千年的时光来发展艺术造诣”,虽然有些人着迷于电脑将来可能创作出新颖而又精妙的作品,正如人类的艺术家一样。到目前为止,只有一台机器几乎做到了。作曲家David Cope写出了一个叫音乐智能实验(EMI)的程序。它不仅仅能仿作Cope的曲风,连最负盛名的古典音乐大师如巴赫、肖邦、莫扎特的曲风也能模仿。听众们听着它的作品感动泪流,连古典音乐都没能发觉所听曲目并不是真正的巴赫作品。当然,也不是所有人都买账。有些人比如Wiggins也曾攻击过他的作品是伪科学,并谴责他刻意隐瞒自己软件的运作方式。同时,印第安纳大学的Douglas Hofstadter说EMI的模仿完全有赖于原作者的创作灵感。而当听众们发现真相时,他们通常会对Cope恼羞成怒,有个音乐爱好者甚至要冲上去揍Cope。在这样的争议中,Cope销毁了EMI的关键数据。
But why did so many people love the music, yet recoil when they discovered how it was composed? A study by computer scientist David Moffat of Glasgow Caledonian University provides a clue. He asked both expert musicians and non-experts to assess six compositions. The participants weren’t told beforehand whether the tunes were composed by humans or computers, but were asked to guess, and then rate how much they liked each one. People who thought the composer was a computer tended to dislike the piece more than those who believed it was human. This was true even among the experts, who might have been expected to be more objective in their analyses.
但是为什么人们明明喜欢那些音乐,却又在发现它们的创作方式后感到厌恶呢?格拉斯哥卡里多尼亚大学的电脑科学家David Moffat所做的一个实验为我们提供了一些线索。实验中他请专业的音乐家和非专业人士来评判6部音乐作品。参与者事先都不知道所听曲目是人类创作还是电脑产物,但他们会被要求去揣测,然后给这些作品按喜爱程度评级。如果人们认为某个曲目是电脑产物,他们的喜爱程度就会低于人类创作的曲目。甚至在当中也是如此,我们可能本来会指望他们在分析评价时能够更客观一些。
Where does this prejudice come from? Paul Bloom of Yale University has a suggestion: he reckons part of the pleasure we get from art stems from the creative process behind the work. This can give it an ‘irresistible essence', says Bloom. Meanwhile, experiments by Justin Kruger of New York University have shown that people's enjoyment of an artwork increases if they think more time and effort was needed to create it. Similarly, Colton thinks that when people experience art, they wonder what the artist might have been thinking or what the artist is trying to tell them. It seems obvious, therefore, that with computers producing art, this speculation is cut short - there's nothing to explore. But as technology becomes increasingly complex, finding those greater depths in computer art could become possible. This is precisely why Colton asks the Painting Fool to tap into online social networks for its inspiration: hopefully this way it will choose themes that will already be meaningful to us.
那这种偏见从何而来呢?耶鲁大学的Paul bloom有这样的说法:他认为我们欣赏艺术作品的愉悦有一部分来自于作品背后的创作过程。他说,这能为艺术作品带来一种“不可抵挡的精妙”。同时,纽约大学的 Justin Kruger的实验表明,人们认为如果作者创作该作品时花的时间精力越多,他们就会越享受这个作品。Colton也有相同的看法,他认为当人们欣赏艺术时,他们会思考作者在创作时在想些什么、他们想要传达什么。因此,显而易见的是,当电脑在创作艺术品时,这个思索过程是被腰斩了的—这里没什么可发掘的。但是随着科技变得愈发复杂,也有可能在电脑艺术中找到深层的意义。这正是Colton会让傻瓜绘图一头扎进社交网络里搜寻灵感的原因:希望这样它能找到一些对我们来说已经很有意义的主题。
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