23考研外刊阅读《卫报》双语精读版训练–人工智能真的可以帮助我们与动物交谈吗?

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上期翻译答案

But humans’ relatively recent burning of fossil fuels is pushing global temperatures upward at an exceptionally rapid rate, placing many species on what a new book by science journalist Benjamin von Brackel notes has been called an “escalator to extinction”—and raising the question of whether migration can save them this time.

但是,人类短时间内燃烧化石燃料,推动全球气温以异常快的速度提高,使许多物种进入了科学记者本杰明·冯·布拉克的新书中所称的“走向灭绝的阶梯”,并提出了这次迁徙是否能拯救它们的问题。

placing…现在分词作伴随状语

《本期内容》

双语阅读

Understanding animal vocalisations has long been the subject of human fascination and study. Various primates give alarm calls that differ according to predator; dolphins address one another with signature whistles; and some songbirds can take elements of their calls and rearrange them to communicate different messages. But most expertsstop short ofcalling it a language, as no animal communication meets all the criteria.

长期以来,理解动物的声音一直是人类为之着迷并开展探究的主题。不同的捕食者下,各种灵长类动物发出的警报声也有所不同;海豚用标志性的哨声呼朋引伴;一些鸟类可以从它们的叫声中提取音符并进行重新排列,用以传达不同的信息。但大多数专家都没有将其称为一种语言,因为没有动物的对话能够符合所有标准。

Until recently, decoding has mostly relied onpainstakingobservation. But interest hasburgeonedin applying machine learning to deal with the huge amounts of data that can now be collected by modern animal-borne sensors. “People are starting to use it,” says Elodie Briefer, an associate professor at the University of Copenhagen who studies vocal communication in mammals and birds. “But we don’t really understand yet how much we can do.”

直到现在,解读动物交流的工作还是主要依赖于艰苦的观察。但是,现在由现代动物交流传感器收集的大量数据可以由机器学习来处理,人们对此项应用产生了浓厚的兴趣。“人们开始利用机器学习,”哥本哈根大学研究哺乳动物和鸟类声音交流的副教授艾洛迪·布里芬说。“但我们还不知道我们的收效如何。”

Briefer co-developed an algorithm that analyses piggruntsto tell whether the animal is experiencing a positive or negative emotion. Another, called DeepSqueak, judges whether rodents are in a stressed state based on theirultrasoniccalls. A further initiative – Project CETI(which stands for the Cetacean Translation Initiative) – plans to use machine learning to translate the communication of sperm whales.

布里芬与他人共同开发了一种算法,可以分析猪的咕噜声,来判断动物是否正在经历积极或消极的情绪。另一个名为 “深度吱吱叫” 的方法是根据啮齿动物的超声波叫声判断啮齿动物是否处于压力状态。另一个倡议——CETI 项目(鲸类翻译倡议的简称)——计划使用机器学习来翻译抹香鲸之间的对话。

Another project involves using AI to generate novel animal calls, withhumpbackwhales as a test species. The novel calls – made by splitting vocalisations into micro-phonemes (distinct units of sound lasting ahundredthof a second) and using a language model to “speak” something whale-like – can then beplayed backto the animals to see how they respond.

另一个项目则是利用人工智能产生新的动物叫声,以座头鲸作为测试物种。新叫声——通过将动物叫声划分成微音素(持续百分之一秒的不同声音单位)并使用语言模型“说出”类似鲸鱼的语言——然后播放给动物,观察它们作何反应。

If the AI can identify what makes a random change versus a semantically meaningful one, it brings us closer to meaningful communication, explains Raskin. “It is having the AI speak the language, even though we don’t know what it means yet.”

翻译划线句,长按文末小程序码打卡,答案下期公布~“下一步将让人工智能说这种语言,尽管我们还不知道它的含义。”

本文节选自:The Guardian(卫报)

发布时间:2022.07.31

作者:Zoë Corbyn

原文标题:Can artificial intelligence really help us talk to the animals?

词汇积累

1.painstaking

英/ ˈpeɪnzteɪkɪŋ /美/ ˈpeɪnzteɪkɪŋ /

adj.刻苦的,下苦功的

n.辛苦,勤勉

2.burgeon

英/ ˈbɜːdʒən /美/ ˈbɜːrdʒən /

vi.萌芽, 发芽;迅速增长

n.芽, 嫩枝

3.grunt

英/ ɡrʌnt /美/ ɡrʌnt /

v.(表示不愿意讲话时)发出哼声,嘟哝着说;发出咕噜声

n.(人或动物的)呼噜声,咕哝声;‹非正式>干重体力活工资低的工人;‹美,非正式>(步兵或海军陆战队中的))低等兵;石鲈鱼;‹英,非正式>(尤指机动车辆的)动力;一种浆果面饼甜点

【名】 (Grove)(俄、捷、波、美)格伦特(人名)

4.ultrasonic

英/ ˌʌltrəˈsɒnɪk /

美/ ˌʌltrəˈsɑːnɪk /

简明

柯林斯

adj.[声] 超声的;超音速的

n.超声波

5.humpback

英/ ˈhʌmpbæk /美/ ˈhʌmpbæk /

n.座头鲸;驼背

6.hundredth

英/ ˈhʌndrədθ /美/ ˈhʌndrədθˌˈhʌndrətθ /

adj.第一百的;一百分之一的

n.第一百,第一百个;百分之一

词组搭配

1.stop short of 决定不做某事;未到达;缺乏

2.play out 重放……录音;把球打回对方

写作句总结

原句:Understanding animal vocalisations has long been the subject of human fascination and study.

结构:Understanding XX has long been the subject of XX .

例句:Understanding the meaning of study hard has long been the subject of many young fellows.

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