Добавил:
ivanov666
Опубликованный материал нарушает ваши авторские права? Сообщите нам.
Вуз:
Предмет:
Файл:Текст как средство интерактивного общения. Учебное пособие
.pdf
31
1. Начните думать об истории, которую вы хотите написать (это может
быть история из вашей жизни, просто история из Интернета, книги).
2. Напишите первый вариант истории.
3. Сократите свою историю. Уберите любые слова, которые не являются
абсолютно необходимыми. Сколько в ней слов?
4. Теперь сократите свою историю еще раз. Сколько слов осталось? В
данный момент вам, возможно, потребуется изменить слова или предложения,
чтобы было ровно 50 слов.
Ниже приведены примеры мини-саги на русском языке:
Денисов стоял в фойе Большого зала консерватории перед концертом,
где игралось его новое сочинение и еще его оркестровка Шостаковича.
Улыбаясь, он выдал нам обе партитуры. Вокруг было столько знакомых, и со
всеми хотелось поговорить, но я всё же сделал над собой усилие, проснулся и
крикнул: «Филипп, вставай, пора в школу!»
Почти неделю мне нездоровилось. Ничего не ладилось – ни музыка, ни
рисование. Вчера в отчаянии я даже уничтожил уже готовую картину, ворчал
и кряхтел, чувствуя себя никчёмным стариком, как наш сосед Колин. Но
сегодня всё по-другому: я поправляюсь, и музыка звучит в голове, и мерещатся
новые картины – жизнь опять приобретает смысл.
Правильней было бы сказать, что чувство уважения мы чаще всего
испытываем к людям творческим, независимо от их половой принадлежности
и области, в которой их творчество проявляется. Нетворческий человек вряд
ли способен внушить уважение. Так получилось, что большинство творческих
людей из моего окружения были композиторами, и среди них было довольно
много женщин.
Here are some English examples:
A fisherman had a nice family and lived happily near the beach, fishing only
for their daily needs. One day he met a businessman who said “catch more fish, buy
more boats and run a successful business”. The fisherman answered “then what?”
“Start a family and live by the beach.”
The boy who lived in the countryside came home from university. He wanted
to give his parents a big surprise. At the door, he found his family cold and cheerless.
To support him with his studies, his parents sold all their cattle and led a very poor
and simple life.
“I don’t like robots,” I said to my new boss after a cup of coffee. “I hate them, I
don’t like working with cold machines”.
32
“Perhaps you really should try to open your mind.” My boss put down his cup
and opened his body, then put two new batteries inside.
The task – Write a mini saga. First spend a few minutes thinking of what you
are going to write about. Write your first draft, then spend time editing, cutting out or
adding words until the text has exactly 50 words.
Ideas for mini-sagas:
- a description of a favourite object, place, person;
- a joke, an anecdote, something funny or scary that happened to you;
- a synopsis of a film you have watched or a book you have read;
- a letter to an old school teacher, friend or relative;
- your views on a topic, a newspaper article, a legend, a song, great
adventure, travelling story, police report.
Unit 6
How adults understand what kids are saying
It's not easy to parse young children's words, but adults' beliefs about what
children want to communicate helps make it possible
When babies first begin to talk, their vocabulary is very limited. Often one of
the first sounds they generate is "da," which may refer to dad, a dog, a dot, or nothing
at all.
How does an adult listener make sense of this limited verbal repertoire? A new
study from MIT and Harvard University researchers has found that adults'
understanding of conversational context and knowledge of mispronunciations that
children commonly make are critical to the ability to understand children's early
linguistic efforts.
Using thousands of hours of transcribed audio recordings of children and adults
interacting, the research team created computational models that let them start to
reverse engineer how adults interpret what small children are saying. Models based
on only the actual sounds children produced in their speech did a relatively poor job
predicting what adults thought children said. The most successful models made their
predictions based on large swaths of preceding conversations that provided context
for what the children were saying. The models also performed better when they were
retrained on large datasets of adults and children interacting.
The findings suggest that adults are highly skilled at making these contextbased interpretations, which may provide crucial feedback that helps babies acquire
language, the researchers say.
"An adult with lots of listening experience is bringing to bear extremely
sophisticated mechanisms of language understanding, and that is clearly what
underlies the ability to understand what young children say," says Roger Levy, a
professor of brain and cognitive sciences at MIT. "At this point, we don't have direct
evidence that those mechanisms are directly facilitating the bootstrapping of language
acquisition in young children, but I think it's plausible to hypothesize that they are
making the bootstrapping more effective and smoothing the path to successful
language acquisition by children."
Levy and Elika Bergelson, an associate professor of psychology at Harvard, are
the senior authors of the study, which appears today in Nature Human Behavior. MIT
postdoc Stephan Meylan is the lead author of the paper.
Adult listening skills are critical
While many studies have investigated how children learn to speak, in this
project, the researchers wanted to flip the question and study how adults interpret
what children say.
"While people have looked historically at a number of features of the learner,
and what is it about the child that allows them to learn things from the world, very
little has been done to look at how they are understood and how that might influence
the process of language acquisition," Meylan says.
33
Previous research has shown that when adults speak to each other, they use
their beliefs about how other people are likely to talk, and what they're likely to talk
about, to help them understand what their conversational partner is saying. This
strategy, known as "noisy channel listening," makes it easier for adults to handle the
complex task of deciphering the acoustic sounds they're hearing, especially in
environments where voices are muffled or there is a lot of background noise, or when
speakers have different accents.
In this study, the researchers explored whether adults can also apply this
technique to parsing the often seemingly nonsensical utterances produced by children
who are learning to talk.
"This problem of interpreting what we hear is even harder for child language
than ordinary adult language understanding, which is actually not that easy either,
even though we're very good at it," Levy says.
For this study, the researchers made use of datasets originally generated at
Brown University in the early 2000s, which contain hundreds of hours of transcribed
conversations between children ages 1 to 3 and their caregivers. The data include
both phonetic transcriptions of the sounds produced by the children and the text of
what the transcriber believed the child was trying to say.
The researchers used other datasets of child language (which included about 18
million spoken words) to train computational language models to predict what words
the children were saying in the original dataset, based on the phonetic transcription.
Using neural networks, they created many different models, which varied in the
sophistication of their knowledge of conversational topics, grammar, and children's
mispronunciations. They also manipulated how much of the conversational context
each model was allowed to analyze before making its predictions of what the children
said. Some models took into account just one or two words spoken before the target
word, while others were allowed to analyze up to 20 previous utterances in the
exchange.
The researchers found that using the acoustics of what the child said alone did
not lead to models that were particularly accurate at predicting what adults thought
children said. The models that did best used very rich representations of
conversational topics, grammar, and beliefs about what words children are likely to
say (ball, dog or baby, rather than mortgage, for example). And much like humans,
the models' predictions improved as they were allowed to consider larger chunks of
previous exchanges for context.
1. Text Comprehension
1.1. Answer the following questions:
1. What helped the research team to create the computational models to see how
adults interpret what small children are saying.
2. What are the computational models based on?
3. When do the computational models perform better?
34
4. What was shown in the previous research?
nonsensical
acquisition
original
networks
verbal
partner
computational
utterances
language
dataset
audio
models
context-based
conversations
conversational
interpretations
transcribed
repertoire
5. What is the essence of the strategy “noisy channel listening”?
6. What are computational language models trained?
7. How many words do the datasets of child language include?
8. What was the result of finding that using the acoustics of what the child said
alone?
1.2. Decide if these statement true or false according to the text:
1. When babies first begin to talk, their vocabulary is not very limited.
2. The research team created computational models in order to understand what
small children are saying.
3. These models made a good job in predicting what the children are saying.
4. The most successful models made their predictions based on large swaths of
preceding conversations.
5. The study was made at Cambridge University.
6. The project aim was to investigate how children learn to speak.
7. In the previous research it was shown how other people are likely to talk and
what they are likely to talk about.
8. The problem of interpreting what we hear is even harder for child language
than ordinary adult language understanding.
2. Vocabulary Comprehension
2.1 Match the words in order to get the word combinations used in the text:
35
Neural
recordings
Find the sentences in the text with the following word combinations and translate
them.
2.2. Fill in the gaps with the words given below:
Behavior, datasets, bootstrapping, vocabulary, interpretations, feedback,
mispronunciations, research, experience, channel,
1. The babies’ …………….. is very limited.
2. A new study has found that adults understand conversational context and know
the …………….. that children often make.
3. The findings suggest that adults are highly skilled at making these context-
based ……………...
4. The contextual interpretations are able to provide crucial ……….. that helps
babies acquire language.
5. An adult with lots of listening ………… is bringing to bear extremely
sophisticated mechanisms of language understanding.
6. The mechanisms are making the ………………. more effective and smoothing
the path to successful language acquisition by children.
7. The study appeared in Nature Human ……….
8. Previous …………..has shown the results of babies’ language interpretations.
9. The strategy “noisy ……….. listening” makes it easier for adults to interpret
the sounds.
10. For this study, the researchers made use of ………… originally generated at
Brown University in the early 2000s.
3.1 Find the predicates and define the tense and voice:
3. Grammar Comprehension
1. Previous research has shown that when adults speak to each other, they use their
beliefs about how other people are likely to talk.
2. When babies first begin to talk, their vocabulary is very limited.
3. People have looked historically at a number of features of the learner.
4. We now have this model of an adult listener that we can plug into models of child
learners.
5. The findings suggest that adults are highly skilled at making these context-based
interpretations.
6. The most successful models made their predictions based on large swaths of
preceding conversations.
36
7. The models also performed better when they were retrained on large datasets of
adults and children interacting.
8. The research was funded by the National Science Foundation.
4.1 Find the Participle I and Participle II in the following sentences:
1. Using thousands of hours of transcribed audio recordings of children and adults
interacting, the research team created computational models.
2. Models based on only the actual sounds children produced in their speech did a
relatively poor job predicting what adults thought children said.
3. The most successful models made their predictions based on large swaths of
preceding conversations that provided context for what the children were saying.
4. The models also performed better when they were retrained on large datasets of
adults and children interacting.
5. In this study, the researchers explored whether adults can also apply this
technique to parsing the often seemingly nonsensical utterances produced by
children who are learning to talk.
6. For this study, the researchers made use of datasets originally generated at Brown
University in the early 2000s.
7. The data include both phonetic transcriptions of the sounds produced by the
children and the text of what the transcriber believed the child was trying to say.
8. Using neural networks, they created many different models.
5. Discussion Part
Now you are going to read the rest of the article.
Before you start reading try to guess the essence of a feedback system which will be
described for understanding the kids’ sounds.
A feedback system
The findings suggest that when listening to children, adults base their
interpretation of what a child is saying on previous exchanges that they have had. For
example, if a dog had been mentioned earlier in the conversation, "da" was more
likely to be interpreted by an adult listener as "dog."
This is an example of a strategy that humans often use in listening to other
adults, which is to base their interpretation on "priors," or expectations based on prior
experience. The findings also suggest that when listening to children, adult listeners
incorporate expectations of how children commonly mispronounce words, such as
"weed" for "read."
The researchers now plan to explore how adults' listening skills, and their
subsequent responses to children, may help to facilitate children's ability to learn
language.
37
"Most people prefer to talk to others, and I think babies are no exception to
this, especially if there are things that they might want, either in a tangible way, like
milk or to be picked up, but also in an intangible way in terms of just the spotlight of
social attention," Bergelson says. "It's a feedback system that might push the kid,
with their burgeoning social skills and cognitive skills and everything else, to
continue down this path of trying to interact and communicate."
One way the researchers hope to study this interplay between child and adult is
by combining computational models of how children learn language with the new
model of how adults respond to what children say.
"We now have this model of an adult listener that we can plug into models of
child learners, and then those learners can leverage the feedback provided by the
adult model," Meylan says. "The next frontier is trying to understand how kids are
taking the feedback that they get from these adults and build a model of what these
children expect that an adult would understand."
The research was funded by the National Science Foundation, the National
Institutes of Health, and a CONVO grant to MIT's Department of Brain and
Cognitive Sciences from the Simons Center for the Social Brain.
There are some questions for discussion:
1. Do you think that adults’ listening skills and their subsequent responses may
really help to facilitate children’s ability to learn language?
2. In your opinion, do the adults’ ability better to understand kids will help them in
the process of communication with each other?
3. Do the children’s’ speaking skills become better developed after the interaction
with the adults?
4. Do the children always copy the behavior model of the adults?
5. Will the conducted research help to overcome mispronunciation of words by the
kids?
6. What is the described feedback about?
7. Are such researches really useful?
Now you have to fill the gap in the text, choosing from the list below:
Facilitate, skills, mispronounce, feedback, computational, frontier, communicate,
interpretation, conversation, strategy.
A feedback system
The findings suggest that when listening to children, adults base their ……….
of what a child is saying on previous exchanges that they have had. For example, if a
dog had been mentioned earlier in the …………., "da" was more likely to be
interpreted by an adult listener as "dog."
38
This is an example of a ……….. that humans often use in listening to other
adults, which is to base their interpretation on "priors," or expectations based on prior
experience. The findings also suggest that when listening to children, adult listeners
incorporate expectations of how children commonly …………… words, such as
"weed" for "read."
The researchers now plan to explore how adults' listening ………., and their
subsequent responses to children, may help to ……….. children's ability to learn
language.
"Most people prefer to talk to others, and I think babies are no exception to
this, especially if there are things that they might want, either in a tangible way, like
milk or to be picked up, but also in an intangible way in terms of just the spotlight of
social attention," Bergelson says. "It's a ………… system that might push the kid,
with their burgeoning social skills and cognitive skills and everything else, to
continue down this path of trying to interact and …………….."
One way the researchers hope to study this interplay between child and adult is
by combining ………….. models of how children learn language with the new model
of how adults respond to what children say.
"We now have this model of an adult listener that we can plug into models of
child learners, and then those learners can leverage the feedback provided by the
adult model," Meylan says. "The next …………. is trying to understand how kids are
taking the feedback that they get from these adults and build a model of what these
children expect that an adult would understand."
The research was funded by the National Science Foundation, the National
Institutes of Health, and a CONVO grant to MIT's Department of Brain and
Cognitive Sciences from the Simons Center for the Social Brain.
39
Unit 7
In the 1800s, some of the strongest earthquakes in recorded U.S. history struck
North America's continental interior. Almost two centuries later, the central and
eastern United States may still be experiencing aftershocks from those events, a new
study finds.
When an earthquake strikes, smaller quakes known as aftershocks can continue
to shake the area for days to years after the original earthquake occurred. These
smaller quakes decrease over time and are part of the fault's readjustment process
following the original quake. While aftershocks are smaller in magnitude than the
main shock, they can still damage infrastructure and impede recovery from the
original earthquake.
"Some scientists suppose that contemporary seismicity in parts of stable North
America are aftershocks, and other scientists think it's mostly background
seismicity," said Yuxuan Chen, a geoscientist at Wuhan University and lead author of
the study. "We wanted to view this from another angle using a statistical method."
The study was published in the Journal of Geophysical Research: Solid
Earth, AGU's journal dedicated to research on the structure, evolution and
deformation of the interior of our planet.
Regions near these historic earthquakes' epicenters are still seismically active
today, so it's possible that some modern earthquakes could be long-lived aftershocks
of past quakes. However, they could also be foreshocks that precede larger
earthquakes or background seismicity, which is the normal amount of seismic activity
for a given region.
According to the U.S. Geological Survey (USGS), there's no way to distinguish
foreshocks from background seismicity until a larger earthquake strikes, but scientists
can still discern aftershocks. Thus, identifying the cause of modern earthquakes is
important for understanding these regions' future disaster risk, even if current seismic
activity is causing little to no damage.
The team focused on three historic earthquake events estimated to range from
magnitude 6.5-8.0: an earthquake near southeastern Quebec, Canada, in 1663; a trio
of quakes near the Missouri-Kentucky border from 1811 to 1812; and an earthquake
from Charleston, South Carolina, in 1886. These three events are the largest
earthquakes in stable North America's recent history -- and larger quakes trigger more
aftershocks.
The stable continental interior of North America is located far from plate
boundaries and has less tectonic activity than regions close to plate boundaries, such
as North America's west coast. As a result, the three study areas don't encounter
earthquakes often, raising even more questions about the origins of their modern
seismicity.
To figure out if some of today's earthquakes are long-lived aftershocks, the
team first needed to determine which modern quakes to focus their efforts on.
Aftershocks cluster around the original earthquake's epicenter, so they included
earthquakes within a 250-kilometer (155-mile) radius of the historic epicenters. They
40
Соседние файлы в предмете [НЕСОРТИРОВАННОЕ]