首页
外语
计算机
考研
公务员
职业资格
财经
工程
司法
医学
专升本
自考
实用职业技能
登录
考研
A computer model has been developed that can predict what word you are thinking of. (41) Researchers led by Tom Mitchell of C
A computer model has been developed that can predict what word you are thinking of. (41) Researchers led by Tom Mitchell of C
admin
2011-03-11
78
问题
A computer model has been developed that can predict what word you are thinking of. (41) Researchers led by Tom Mitchell of Carnegie Mellon University in Pittsburgh, Pennsylvania, "trained" a computer model to recognize the patterns of brain activity associated with 60 images, each of which represented a different noun, such as "celery" or "aeroplane".
(42) . Words such as "hammer", for example, axe known to cause movement-related areas of the brain to light up; on the other hand, the word "castle" triggers activity in regions that process spatial information. Mitchell and his colleagues also knew that different nouns are associated more often with some verbs than with others--the verb "eat", for example, is more likely to be found in conjunction with "celery" than with "aeroplane". The researchers designed the model to try and use these semantic links to work out how the brain would react to particular nouns. They fed 25 such verbs into the model.
(43) . The researchers then fed the model 58 of the 60 nouns to train it. For each noun, the model sorted through a trillion-word body of text to find how it was related to the 25 verbs, and how that related to the activation pattern. After training, the models were put to the test. Their task was to predict the pattern of activity for the two missing words from the group of 60, and then to deduce which word was which. On average, the models came up with the right answer more than three-quarters of the time.
The team then went one step further, this time training the models on 59 of the 60 test words, and then showing them a new brain activity pattern and offering them a choice of 1 001 words to match it. The models performed well above chance when they were made to rank the 1001 words according to how well they matched the pattern. The idea is similar to another "brain-reading" technique. (44) . It shouldn’t be too difficult to get the model to choose accurately between a larger number of words, says John-Dylan Haynes.
An average English speaker knows 50 000 words, Mitchell says, so the model could in theory be used to select any word a subject chooses to think of. Even whole sentences might not be too distant a prospect for the model, saysMitchell. "Now that we can see individual words, it gives the scaffolding for starting to see what the brain does with multiple words as it assembles them," he says. (45)
Models such as this one could also be useful in diagnosing disorders of language or helping students pick up a foreign language. In semantic dementia, for example, people lose the ability to remember the meanings of things--shown a picture of a chihuahua, they can only recall "dog", for example--but little is known about what exactly goes wrong in the brain. "We could look at what the neural encoding is for this," says Mitchell.
[A] The team then used functional magnetic resonance imaging (FMRI) to scan the brains of 9 volunteers as they looked at images of the nouns
[B] The study can predict what picture a person is seeing from a selection of more than 100, reported by Nature earlier this year
[C] The model may help to resolve questions about how the brain processes words and language, and might even lead to techniques for decoding people’s thoughts
[D] This gives researchers the chance to understand the "mental chemistry" that the brain does when it processes such phrases, Mitchell suggests
[E] This research may be useful for a human computer interface but does not capture the complex network that allows a real brain to learn and use words in a creative way
[F] The team started with the assumption that the brain processes words in terms of how they relate to movement and sensory information
[G] The new model is different in that it has to look at the meanings of the words, rather than just lower-level visual features of a picture
选项
答案
D
解析
本题位于段落的最后,所以应结合上文找出正确答案。本段说明这个模型的意义及研究的前景,指出平均每个说英语的人会50000个单词,那么在理论上它应该能选择出主体所想的任何单词。本空的前一句提到,这就为开始研究大脑在组合单词时如何处理它们提供了支撑。那么所填的句子应该涉及“组合单词”的信息。在[B]、[D]和[E]这三个选项中,涉及此信息的只有[D],故为正确答案。[B]从整体上说了研究的意义,[E]说明了研究的不足,与该段的整体内容不符,故都排除。
转载请注明原文地址:https://www.kaotiyun.com/show/i9p4777K
0
考研英语一
相关试题推荐
Humanshavealteredtheworld’sclimateby(1)_____heat-trappinggasessincealmostthebeginningofcivilizationandevenprev
Humanshavealteredtheworld’sclimateby(1)_____heat-trappinggasessincealmostthebeginningofcivilizationandevenprev
Writeonthefollowingtopic:DevelopingEconomyorProtectingtheEnvironment1.一些人认为发展经济最重要。2.另一些则认为保护环境更重要。3.
TheStudentUnionofyouruniversityisgoingtohostaNewYearparty.OnbehalfoftheStudentUnion,writeProfessorGeorgeK
Atsomepointduringtheireducation,biologystudentsaretoldaboutaconversationinapubthattookplaceover50yearsago.
Almostexactlyayearago,inasmallvillageinNorthernIndia,AndreaMillinerwasbittenonthelegbyadog."Itmusthave(
Skilledcomputercriminalscanbreakintoacomputersystem______.Whatdosethelastparagraphimply?
Manyteachersbelievethattheresponsibilitiesforlearningliewiththestudent.(1)_____alongreadingassignmentisgiven,
Therewasatimewhenparentswhowantedaneducationalpresentfortheirchildrenwouldbuyatypewriter,aglobeoranencyclo
Bysaying"thegoldenriversarebeingdiverted",theauthormeansWhatcanbepredictedfromthelastparagraph?
随机试题
A.多有眶下区弥漫性水肿B.以下颌角为中心的咬肌区红肿伴明显张口受限C.先有牙痛史,继而出现张口受限D.多出现颌下三角区的红肿E.多出现颌下、口底广泛水肿翼下颌间隙感染
龈上菌斑定义正确的是
关于降钙素的说法错误的是()。
下列业务,可以免征增值税的项目有()。
运输企业财务管理的内容主要包括()。
同住一个小区的三位同事早上7:30同时出门上班,甲自驾车,乙乘坐公交车,丙骑自行车。如果他们的路程相同,甲8:00到达单位,乙8:30到达单位,丙8:15到达单位,则他们的平均速度比是()。
《九章律》
甲为自己房屋使用的便利,与乙签订地役权合同,约定五年内乙不得加盖楼房,甲支付5万元。合同签订后,双方办理了登记手续。三年后甲去世,房屋由丙继承。同年,乙将楼房卖给丁,随后丁加盖楼房,遭丙阻止。在本案中()。(2013年多选47)
E-R图中用来表示实体的图形是()。
Thisisthereason______anaeroplanecan’tflyinspace.
最新回复
(
0
)