【大問3 適語補充+内容理解】
次の文章に関して、空欄補充問題と読解問題の二つがあります。
まず、[61]から[80]の空所を埋めるのに、文脈的に最も適切な語を1から3の中から選び、その番号を(61)から(80)にマークしなさい。
次に、内容に関する[81]から[90]の設問には、1から4の番号が付されています。そのうち、文章の内容からみて最も適切なものを選び、その番号を解答欄(81)から(90)にマークしなさい。
Paragraph1 In the biblical story about the Tower of Babel, people conspired to build a city and tower that would reach heaven. Their creator observed, “And now nothing will be restrained from them, which they have imagined to do.” According to this story, God thwarted this effort by creating [61](1. disparate 2. shared 3. divine) languages so that they could no longer collaborate.
Paragraph2 In our modern times, we're experiencing a state of [62](1. unreliable 2. unprecedented 3. unassuming) connectivity thanks to technology. However, we're still living under the shadow of the Tower of Babel. Language remains a barrier in business and marketing. Even though technological devices can quickly and easily connect, humans from different [63](1. backgrounds 2. parts 3. slices) of the world often can't.
Paragraph3 Translation agencies [64](1. meet halfway 2. step in 3. negotiate terms), making presentations, contracts, instructions, and promotional materials comprehensible to all intended recipients. Some agencies also offer "localization” expertise. For instance, if a company is marketing in Quebec, the [65](1. languages 2. translators 3. advertisements) need to be in Québécois French, not European French. However, risk-averse companies may be reluctant to invest in these translations. Consequently, these ventures haven't achieved full market penetration.
Paragraph4 Global markets are waiting, but Al-powered language translation isn't ready yet, [66](1. besides 2. following 3. despite) recent advancements in natural language processing and sentiment analysis. AI still has difficulties processing requests in one language, without the additional complications of translation. In November 2016, Google added a neural network to its translation tool. However, some of its translations are still socially and grammatically odd. I spoke to technologists and a language professor to find out why.
Paragraph5 “[67](1. For 2. To 3. With) Google's credit, they made a pretty massive improvement that appeared almost overnight. You know, I don't use it as much. I will say this. Language is hard,” said Michael Housman, chief data science officer at RapportBoost.AI and faculty member of Singularity University. He [68](1. explained 2. planned 3. rejected) that the ideal scenario for machine learning and artificial intelligence is something with fixed rules and a clear-cut measure of success or failure. He named chess as an obvious example, and noted machines were able to beat the best human Go player. This happened faster than anyone anticipated because of the game's very clear rules and [69](1. infinite 2. limited 3. subsequent) set of moves.
Paragraph6 Housman [70](1. negotiated 2. contradicted 3. elaborated), “Language is almost the opposite of that. There aren't as clearly-cut and defined rules. The conversation can go in an infinite number of different directions. And then of course, you need labeled data. You need to tell the machine to do it right or wrong.” Housman noted that it's [71](1. inadvertently 2. inherently 3. intermittently) difficult to assign these informative labels. “Two translators won't even agree on whether it was translated properly or not,” he said. “Language is kind of the wild west, in terms of data.”
Paragraph7 Google's technology is now able to consider the entirety of a sentence, as opposed to merely translating individual words. Still, the glitches [72](1. linger 2. interfere 3. break). I asked Dr. Jorge Majfud, Associate Professor of Spanish, Latin American Literature, and International Studies at Jacksonville University, to explain why consistently accurate language translation has thus far [73] (1. eluded 2. undermined 3. improved) AI. He replied, “The problem is that considering the entire sentence is still not enough. The same way the meaning of a word depends on the rest of the sentence an in Spanish), the meaning of a sentence depends on the rest of the paragraph and the rest of the text, as the meaning of a text depends on a larger context called culture, speaker intentions, etc.”
Paragraph8 He noted that sarcasm and irony only make sense within this widened context. Similarly, idioms can be problematic for automated translations. “Google translation is a good that is, not to substitute human learning or understanding,” he said, before [74](1. setting 2. taking 3. offering) examples of mistranslations that could occur. “Months ago, I went to buy a drill at Home Depot and I read a sign under a machine: “Saw machine.' Right below it, the Spanish translation: “La
máquina vió,' which means, “The machine did see it.' Saw, not as a noun but as a verb in the preterit form,” he explained.
Paragraph9 Dr. Majfud warned, “We should be aware of the fragility of their ‘interpretation’. Because to translate is basically to interpret, not just an idea but a feeling. Human feelings and ideas that only humans can understand - and sometimes not even we, humans, understand other humans.” He noted that cultures, gender, and even age can pose barriers to [75](1. his 2. this 3. its) understanding and also contended that an over-reliance on technology is leading to our cultural and political decline. Dr. Majfud mentioned that Argentinean writer Julio Cortázar used to [76](1. refer to 2. explain 3. implicate) dictionaries as “cemeteries”. He suggested that automatic translators could be called “zombies”.
Paragraph10 Erik Cambria is an academic AI researcher and assistant professor at Nanyang Technological University in Singapore. He mostly [77](1. advises against 2. focuses on 3. reprimands) natural language processing, which is at the core of AI-powered language translation. Like Dr. Majfud, he sees the complexity and associated risks. “There are so many things that we unconsciously do when we read a piece of text,” he told me. Reading comprehension requires multiple [78](1. interrelated 2. unrelated 3. overrated) tasks, which haven't been accounted for in past attempts to automate translation. Cambria continued, “The biggest issue with machine translation today is that we tend to go from the syntactic form of a sentence in the input language to the syntactic form of that sentence in the target language. That's not what we humans do. We first decode the meaning of the sentence in the input language and then we encode that meaning into the target language.”
Paragraph11 [79](1. Contrastingly 2. Otherwise 3. Additionally), there are cultural risks involved with these translations. Dr. Ramesh Srinivasan, Director of UCLA's Digital Cultures Lab, said that new technological tools sometimes reflect underlying biases. “There tend to be two parameters that shape how we design ‘intelligent systems.' One is the values and you might say biases of those that create the systems. And the second is the world, if you will, that they learn from,” he told me. “If you build AI systems that reflect the biases of their creators and of the world more largely, you get some, occasionally, [80](1. spectacular failures 2. vertical challenges 3. howling successes).” Dr. Srinivasan said translation tools should be transparent about their capabilities and limitations. He said, “You know, the idea that a single system can take languages that I believe are very diverse semantically and syntactically from one another and claim to unite them or universalize them, or essentially make them sort of a singular entity, it's a misnomer, right?”
David Pring Mill. Why Hasn't AI Mastered Language Translation.
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[81] What does the author mean by “we're still living under the shadow of the Tower of Babel” in the 2nd paragraph?
1 Technology continues to impact the way people communicate with each other.
2 Language differences persist as a stumbling block to communication.
3 Religion and culture are still responsible for the variety of languages in the world.
4 Language variation has forced societies to collaborate on translation AI.
[82] According to the article, machine learning and artificial intelligence work best when
1 humans are given control only if machines cannot function autonomously.
2 there is flexibility in identifying solutions for complex tasks.
3 their use involves established guidelines and a definite way to assess outcomes.
4 the resulting translations are influenced by the culture and beliefs of people.
[83] What was the effect of the 2016 change in Google Translate?
1 It is now able to understand the cultural significance of a sentence.
2 It can now analyze the entire context of a passage when translating.
3 It is now able to translate the meaning of each word in a sentence carefully.
4 It can now analyze the whole sentence when translating.
[84] What is meant by “Language is kind of the wild west, in terms of data” in the 6th paragraph?
1 Automated data benefits from inconsistent labels.
2 Language displays simple and lawless behaviors.
3 Western culture dictates most rules for translation.
4 Language is seldom constrained by clear rules.
[85] In the 9th paragraph, Dr. Jorge Majfud argues that
1 machine translation errors will no longer occur in the foreseeable future.
2 excessive dependence on technology will have identifiable consequences.
3 conveying uniquely human feelings and emotions will become easier for machines.
4 divisions between already fragile cultures will be reinforced by technology.
[86] According to the article, sarcasm and idioms are difficult to translate by automated systems because their meaning depends on
1 the logical meaning in the context of the sentence.
2 variables that are not readily apparent based on the text itself.
3 the organizational pattern of the whole text.
4 individual interpretations without any frame of reference.
[87] According to Erik Cambria, what is the biggest problem with machine translation today?
1 It doesn't go beyond the syntax of both languages involved in the translation.
2 It attempts to analyze language in the way the human brain does but fails.
3 It works via the decoding and encoding processes rather than direct translation.
4 It places emphasis on sentence comprehensibility over grammatical accuracy.
[88] What are the “two parameters” that are described in the 11th paragraph?
1 Human intelligence and the conflicting values adopted by machines.
2 Syntactic diversity and semantic clarity in automated translation platforms.
3 The corresponding successes and failures of technological advancements.
4 The personal and societal dispositions that influence AI systems.
[89] For which text type would current automated translation technology be most effective?
1 Classic works of literature.
2 Lyrics from popular music artists.
3 Product descriptions for online sellers.
4 Subtitles for comedies.
[90] Which of the following would be the best title for this article?
1 Why Doesn't AI Get the Recognition It Deserves?
2 Machine Translation Is Ready for the Future
3 Why Hasn't Al Mastered Language Translation?
4 Google Translate Makes Language Translation Easy
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