Pratica di Shadowing: Noam Chomsky: Language, Cognition, and Deep Learning | Lex Fridman Podcast #53 - Impara a parlare inglese con i video
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The following is a conversation with Noam Chomsky.
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He's truly one of the great minds of our time
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and is one of the most cited scholars in the history of our civilization.
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He has spent over 60 years at MIT and recently also joined the University of Arizona where we met for this conversation.
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But it was at MIT about four and a half years ago when I first met Noam.
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My first few days there, I remember getting into an elevator at Stata Center, pressing the button for whatever floor,
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looking up and realizing it was just me and Noam Chomsky riding the elevator.
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Just me and one of the seminal figures of linguistics, cognitive science, philosophy, and political thought in the past century, if not ever.
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I tell that silly story
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because I think life is made up of funny little defining moments
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that you never forget for reasons that may be too poetic to try and explain.
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That was one of mine.
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Noam has been an inspiration to me and millions of others.
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It was truly an honor for me to sit down with him in Arizona.
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I traveled there just for this conversation.
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And in a rare, heartbreaking moment, after everything was set up and tested,
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the camera was moved and accidentally the recording button was pressed, stopping the recording.
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So I have good audio of both of us, but no video of Noam.
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Just the video of me and my sleep -deprived but excited face
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that I get to keep as a reminder of my failures.
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Most people just listen to this audio version for the podcast as opposed to watching it on YouTube.
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But still, it's heartbreaking for me.
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I hope you understand and still enjoy this conversation as much as I did.
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The depth of intellect that Noam showed and his willingness to truly listen to me.
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A silly -looking Russian in a suit.
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it was humbling and something I'm deeply grateful for.
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As some of you know, this podcast is a side project for me,
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where my main journey and dream is to build AI systems that do some good for the world.
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This latter effort takes up most of my time, but for the moment has been mostly private.
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But the former, the podcast, is something I put my heart and soul into, and I hope you feel that, even when they screw things up.
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I recently started doing ads at the end of the introduction.
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I'll do one or two minutes after introducing the episode
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and never any ads in the middle that break the flow of the conversation.
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I hope that works for you.
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It doesn't hurt the listening experience.
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This is the Artificial Intelligence Podcast.
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If you enjoy it, subscribe on YouTube, give it five stars on Apple Podcasts,
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support it on Patreon, or simply connect with me on Twitter at Lex Friedman, spelled F -R -I -D -M -A -N.
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which again is an organization that I've personally seen inspire girls and boys to dream of engineering a better world.
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And now, here's my conversation with Noam Chomsky.
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I apologize for the absurd philosophical question, but if an alien species or to visit
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Earth, do you think we would be able to find a common language or protocol of communication with them?
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There are arguments to the effect that we could.
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In fact, one of them was Marv Minsky's.
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Back about 20 or 30 years ago, he performed a brief experiment with a student of his,
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Dan Bob Rowe they essentially ran the simplest possible Turing machines just free to see what would happen.
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And most of them crashed, either got into an infinite loop or stopped.
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The few that persisted essentially gave something like arithmetic.
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And his conclusion from that was that if some alien species developed higher intelligence,
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they would at least have arithmetic.
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They would at least have what the simplest computer would do.
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And in fact, he didn't know that at the time,
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but the core principles of natural language are based on operations
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which yield something like arithmetic in the limiting case and the minimal case.
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So it's conceivable
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that a mode of communication could be established based on the core properties of human language and the core properties of arithmetic,
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which maybe are universally shared.
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So it's conceivable.
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What is the structure of that language,
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of language as an internal system inside our mind versus an external system as it's expressed?
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It's not an alternative.
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It's two different concepts of language.
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Different.
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It's a simple fact that there's something about you, a trait of yours, part of the organism,
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you, that determines that you're talking English and not Tagalog, let's say.
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So there is an inner system.
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It determines the sound and meaning of the infinite number of expressions of your language.
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it's localized it's not on your foot obviously it's in your brain
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if you look more closely it's in specific configurations of your brain
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and that's essentially like the internal structure of your laptop whatever programs
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it has are in there now one of the things
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you can do with language it's a marginal thing in fact is use it to externalize what's in your head
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Actually, most of your use of language is thought, internal thought.
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But you can do what you and I are now doing.
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We can externalize it.
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Well, the set of things that we're externalizing are an external system.
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They're noises in the atmosphere.
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And you can call that language in some other sense of the word.
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But it's not a set of alternatives.
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These are just different concepts.
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So how deep do the roots of language go in our brain?
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our mind?
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Is it yet another feature like vision, or is it something more fundamental from which everything else springs in the human mind?
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Well, in a way, it's like vision.
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There's something about our genetic endowment that determines that we have a mammalian rather than an insect visual system.
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And there's something in our genetic endowment that determines that we have a human language faculty.
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No other organism has anything remotely similar.
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So, in that sense, it's internal.
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Now, there is a long tradition, which I think is valid going back centuries to the early scientific revolution,
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at least, that holds that language is sort of the core of human cognitive nature.
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It's the source.
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It's the mode for constructing thoughts and expressing them
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that is what forms thought and it's got fundamental creative capacities it's free independent unbounded
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and so on and undoubtedly I think the basis for creative capacities and the other
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remarkable human capacities that lead to the unique achievements and not so great achievements of the species.
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The capacity to think and reason, do you think that's deeply linked with language?
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Do you think the way we, the internal language system is essentially the mechanism by which we also reason internally?
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It is undoubtedly the mechanism by which we reason.
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There may also be other – there are undoubtedly other faculties involved in reasoning.
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We have a kind of scientific faculty.
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Nobody knows what it is.
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But whatever it is that enables us to pursue certain lines of endeavor
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and inquiry and to decide what makes sense and doesn't make sense
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and to achieve a certain degree of understanding of the world.
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That uses language but goes beyond it.
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just as using our capacity for arithmetic is not the same as having the capacity.
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The idea of capacity, our biology, evolution, you've talked about it defining essentially our capacity, our limit, and our scope.
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Can you try to define what limit and scope are?
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And the bigger question, do you think it's.. possible to find the limit of human cognition?
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Well, that's an interesting question.
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It's commonly believed, most scientists believe, that human intelligence can answer any question in principle.
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I think that's a very strange belief.
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If we're biological organisms, which are not angels,
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then our capacities ought to have scope and limits which are interrelated.
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Can you define those two terms?
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Well, let's take a concrete example.
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Your genetic endowment determines that you can have a male individual system, arms and legs and so on,
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and therefore become a rich, complex organism.
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But if you look at that same genetic endowment, it prevents you from developing in other directions.
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There's no kind of experience which would yield the embryo to develop an insect visual system
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or to develop wings instead of arms.
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So the very endowment that confers richness and complexity also sets bounds on what can be attained.
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Now, I assume that our cognitive capacities are part of the organic world.
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Therefore, they should have the same properties.
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If they had no built -in capacity to develop a rich and complex structure, we would have understand nothing.
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Just as if your genetic endowment did not compel you to develop arms and legs,
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you would just be some kind of random amoeboid creature with no structure at all.
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So I think it's plausible to assume that there are limits, and I think we even have some evidence as to what they are.
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For example, there's a classic moment in the history of science at the time of Newton.
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From Galileo to Newton, modern science developed on a fundamental assumption, which Newton also accepted.
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Namely, that the world, the entire universe, is a mechanical object.
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And by mechanical, they meant something like the kinds of artifacts that were being developed by skilled artisans all over Europe,
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gears, levers, and so on.
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And their belief was, well, the world is just a more complex variant of this.
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Newton, to his astonishment and distress, proved that there are no machines,
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that there's interaction without contact.
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His contemporaries like Leibniz and Huygens just dismissed this as returning to the mysticism of the neo -scholastics.
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Newton agreed.
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As you said, it is totally absurd.
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No person of any scientific intelligence could ever accept this for a moment.
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In fact, he spent the rest of his life trying to get around it somehow, as did many other scientists.
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That was the very criterion of intelligibility for, say, Galileo or Newton.
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Theory did not produce an intelligible world unless you could duplicate it in a machine.
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He said, you can't.
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There are no machines, any.
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Finally, after a long struggle, it took a long time, scientists just accepted this as common sense.
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But that's a significant moment.
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That means they abandoned the search for an intelligible world.
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And the great philosophers of the time understood that very well.
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So, for example, David Hume, in his encomium to Newton, wrote that who was the greatest thinker ever and
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so on he said that he unveiled the secret many of the secrets of nature
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but by showing the imperfections of the mechanical philosophy mechanical science he left us with he showed
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that there are mysteries which ever will remain
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and science just changed its its goals it abandoned the mysteries it can't solve it we'll put it side.
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We only look for intelligible theories.
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Newton's theories were intelligible.
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It's just what they described wasn't.
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Well, Locke said the same thing.
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I think they're basically right.
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And if so, that showed something about the limits of human cognition.
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We cannot attain the goal of understanding the world, of finding an intelligible world.
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This mechanical philosophy, Galileo to Newton,
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there's a good case that can be made that that's our instinctive conception of how things work.
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So if, say, infants are tested with things, if this moves and then this moves,
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they kind of invent something that must be invisible that's in between them that's making them move and so on.
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Yeah, we like physical contact.
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Something about our brain seeks...
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Makes us want a world like that, just like it wants a world that has regular geometric figures.
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So, for example, Descartes pointed this out,
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that if you have an infant who's never seen a triangle before and you draw a triangle,
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the infant will see a distorted triangle, not whatever crazy figure it actually is,
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three lines not coming quite together, one of them a little bit curved and so on.
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We just impose a conception of the world in terms of perfect geometric objects.
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It's now been shown that it goes way beyond that, that if you show on a tachistoscope, let's say, a couple of lights shining,
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you do it three or four times in a row, what people actually see is a rigid object in motion, not whatever's there.
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We all know that from a television set, basically.
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So that gives us hints of potential limits to our cognition.
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I think it does, but it's a very contested view.
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If you do a poll among scientists, it's impossible.
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We can understand anything.
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Let me ask and give me a chance with this.
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So I just spent a day at a company called Neuralink.
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And what they do is try to design what's called the brain -machine, brain -computer interface.
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So they try to do thousands of readings in the brain, be able to read what the neurons are firing,
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and then stimulate back, so two -way.
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Do you think their dream is to expand the capacity of the brain to attain information,
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sort of increase the bandwidth of which we can search Google kind of thing?
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Do you think our cognitive capacity might be expanded,
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our linguistic capacity, our ability to reason might be expanded by adding a machine into the picture?
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It can be expanded in a certain sense, but a sense that was known thousands of years ago.
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A book expands your cognitive capacity.
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Okay, so this could expand it too.
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But it's not a fundamental expansion.
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It's not totally new things could be understood.
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Well, nothing that goes beyond our native cognitive capacities, just like you can't turn the visual system into an insect system.
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Well, I mean, the thought is perhaps you can't directly, but you can map.
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You could, but we already know that without this experiment.
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You could map what a bee sees and present it in a form so that we could follow it.
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In fact, every bee scientist does that.
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But you don't think there's something greater than bees that we can map and then all of a sudden discover something,
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be able to understand a quantum world, quantum mechanics, be able to start to be able to make sense.
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Students at MIT study and understand quantum mechanics.
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But they always reduce it to the infant, the physical.
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I mean, they don't really understand it.
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Oh, you don't, there's things.
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That may be another area where there's just a limit to understanding.
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We understand the theories, but the world that it describes doesn't make any sense.
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So, you know, the experiment, Schrodinger's cat, for example, can understand the theory, but as Schrodinger pointed out, it's an unintelligible world.
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One of the reasons why Einstein was always very skeptical about quantum theory.
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He described himself as a classical realist in one's intelligibility.
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He has something in common with infants in that way.
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So, back to linguistics, if you could humor me, what are the most beautiful or fascinating aspects of language
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or ideas in linguistics or cognitive science that you've seen in a lifetime of studying language and studying the human mind?
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Well, I think the deepest property of language.
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and puzzling property that's been discovered is what is sometimes called structure dependence.
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We now understand it pretty well, but it was puzzling for a long time.
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I'll give you a concrete example.
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So suppose you say the guy who fixed the car carefully packed his tools.
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It's ambiguous.
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He could fix the car carefully or carefully pack his tools.
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Suppose you put, carefully in front, carefully the guy who fixed the car packed his tools.
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Then it's carefully packed, not carefully fixed, and in fact you do that even if it makes no sense.
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So suppose you say, carefully the guy who fixed the car is tall.
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You have to interpret it as carefully he's tall, even though that doesn't make any sense.
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And notice that that's a very puzzling fact because you're relating carefully not to the linearly closest verb,
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but to the linearly more remote verb.
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A linear approach of closeness is an easy computation.
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But here you're doing a much more, what looks like a more complex computation.
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You're doing something that's taking you essentially to the more remote thing.
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if you look at the actual structure of the sentence where the phrases are
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and so on turns out you're picking out the structurally closest thing
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but the linearly more remote thing but notice that what's linear is 100 % of what you hear you never hear structure,
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you can't so what you're doing is and instantly this is universal all constructions, all languages
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and what we're compelled to do is carry out what looks like the more complex computation on material
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that we never hear and we ignore 100 % of what we hear and the simplest computation.
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By now there's even a neural basis for this that's somewhat understood
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and there's good theories by now that explain why it's true.
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That's a deep insight into the surprising nature of language with many consequences.
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Let me ask you about a field of machine learning, deep learning.
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There's been a lot of progress in neural network -based machine learning in the recent decade.
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Of course, neural network research goes back many decades.
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What do you think are the limits of deep learning, of neural network -based machine learning?
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Well, to give a real answer to that, you'd have to understand the exact processes that are taking place.
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And those are pretty opaque.
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So it's pretty hard to prove a theorem about what can be done and what can't be done.
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But I think it's reasonably clear.
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I mean, putting technicalities aside,
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what deep learning is doing is taking huge numbers of examples and finding some patterns.
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Okay.
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That could be interesting.
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In some areas it is.
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But we have to ask here a certain question.
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Is it engineering or is it science?
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Engineering in the sense of just trying to build something that's useful,
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or science in the sense that it's trying to understand something about elements of the world.
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So it takes a Google parser.
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We can ask that question.
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Is it useful?
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Yeah, it's pretty useful.
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You know, I use a Google translator.
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So on engineering grounds, it's kind of worth having, like a bulldozer.
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Does it tell you anything about human language?
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Zero.
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Nothing.
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And in fact, it's very striking.
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From the very beginning, it's just totally remote from science.
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So what is a Google parser doing?
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It's taking an enormous text, let's say the Wall Street Journal corpus,
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and asking, how close can we come to getting the right description of every sentence in the corpus?
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Well, every sentence in the corpus is essentially an experiment.
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Each sentence that you produce is an experiment, which says, am I a grammatical sentence?
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The answer is usually yes.
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So, most of the stuff in the corpus is grammatical sentences.
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But now, ask yourself, is there any science which takes random experiments, which are carried out for no reason whatsoever,
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and tries to find out something from them?
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Like if you're, say, a chemistry PhD student student, you want to get a thesis,
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can you say, well, I'm just going to mix a lot of things together,
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no purpose, and maybe I'll find something that you'd be laughed out of the department.
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Science tries to find critical experiments, ones that answer some theoretical question, doesn't care about coverage of millions of experiments.
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So it just begins by being very remote from science and it continues like that.
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So, the usual question that's asked about, say, a Google parser is how well does it do,
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or some parser, how well does it do on a corpus?
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But there's another question that's never asked.
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How well does it do on something that violates all the rules of language?
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So, for example, take the structure dependence case that I mentioned.
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Suppose there was a language in which you used linear proximity as the mode of interpretation.
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These deep learning had worked very easily on that.
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In fact, much more easily than an actual language.
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Is that a success?
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No, that's a failure.
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From a scientific point of view, it's a failure.
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It shows that we're not discovering the nature of the system at all
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because it does just as well or even better on things that violate the structure of the system.
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And it goes on from there.
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It's not an argument against doing it.
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It is useful to have devices like this.
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So yes, neural networks are kind of approximators that look, there's echoes of the behavioral debates, right?
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Behavioralism.
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More than echoes.
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Many of the people in deep learning say they vindicated.
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Terry Sanyoski, for example, in his recent book says
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This vindicates Skinnerian behaviors and it doesn't have anything to do with it.
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Yes, but I think there's something actually fundamentally different when the data set is huge.
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But your point is extremely well taken.
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But do you think we can learn,
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approximate that interesting complex structure of language with neural networks that will somehow help us understand the science?
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It's possible.
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I mean, you find patterns that you hadn't noticed, let's say, could be.
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In fact, it's very much like a kind of linguistics that's done, what's called corpus linguistics.
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When you, suppose you have some language where all the speakers have died out, but you have records.
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So you just look at the records and see what you can figure out from that.
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It's much better to have actual speakers where you can do critical experiments.
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But if they're all dead, you can't do them.
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So you have to try to see what you can find out from just looking at the data that's around.
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You can learn things.
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Actually, paleoanthropology is very much like that.
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You can't do a critical experiment on what happened two million years ago.
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So you're kind of forced just to take what data's around and see what you can figure out from it.
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Okay, it's a serious study.
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So let me venture into another whole body of work and philosophical question.
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You've said that evil in society arises from institutions, not inherently from our nature.
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Do you think most human beings are good, they have good intent, or do most have the capacity for intentional evil that depends on their upbringing,
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depends on their environment, on the context?
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I wouldn't say that they don't arise from our nature.
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Anything we do arises from our nature.
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And the fact that we have certain institutions, not others, is one mode in which human nature has expressed itself.
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But as far as we know, human nature could yield many different kinds of institutions.
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The particular ones that have developed have to do with historical contingency, who conquered whom and that sort of thing.
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They're not rooted in our nature in the sense that they're essential to our nature.
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So it's commonly argued that these days that something like market systems is just part of our nature.
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But we know from a huge amount of evidence that that's not true.
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There's all kinds of other structures.
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It's a particular fact of a moment of modern history.
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Others have argued that the roots of classical liberalism actually argue that what's called sometimes an instinct for freedom,
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an instinct to be free of domination by illegitimate authority is the core of our nature.
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That would be the opposite of this.
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And we don't know, we just know that human nature can accommodate both kinds.
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If you look back at your life,
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Is there a moment in your intellectual life or life in general that jumps from memory that brought you happiness,
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that you would love to relive again?
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Sure.
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Falling in love, having children.
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What about, so you have put forward into the world a lot of incredible ideas in linguistics,
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in cognitive science in terms of ideas that just excites you when they first came to you,
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that you would love to relive those moments?
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Well, I mean, when you make a discovery about something that's exciting,
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like, say, even the observation of structure dependence and on from that, the explanation for it.
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But the major things just seem like common sense.
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So if you go back to take your question about external and internal language, you go back to, say,
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the 1950s, almost entirely language is regarded as an external object, something outside the mind.
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It just seemed obvious that that can't be true.
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Like I said, there's something about you that determines you're talking English, not Swahili or something.
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But that's not really a discovery.
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That's just an observation that's transparent.
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You might say it's kind of like the 17th century, the beginnings of modern science, 17th century.
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They came from being willing to be puzzled about things that seemed obvious.
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So it seems obvious that a heavy ball of lead will fall faster than a light ball of lead.
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But Galileo was not impressed by the fact that it seemed obvious, so he wanted to know if it's true.
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He carried out experiments, actually thought experiments, never actually carried them out, which showed that it can't be true.
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And out of things like that,
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observations of that kind, why does a ball fall to the ground instead of rising, let's say?
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It seems obvious until you start thinking about it because why does steam rise, let's say.
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I think the beginnings of modern linguistics, roughly in the 50s, are kind of like that,
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just being willing to be puzzled about phenomena that looked, from some point of view, obvious.
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For example, a kind of doctrine, almost official doctrine of structural linguistics in the 50s was
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that languages can differ from one another in arbitrary ways and each one has to be studied
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on its own without any presuppositions.
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In fact, there were similar views among biologists about the nature of organisms,
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that each one is, they're so different when you look at them that almost anything, you could be almost anything.
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Well, in both domains, it's been learned
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that that's very far from true they're very narrow constraints on what could be an organism
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or what could be a language
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but these are you know that's just the nature of inquiry science in general yeah inquiry
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so one of the peculiar things about us human beings is our mortality ernest becker explored
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it in general do you ponder the value of mortality do you think about your own mortality
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I used to when I was about 12 years old.
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I wondered.
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I didn't care much about my own mortality, but I was worried about the fact that if my consciousness disappeared,
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would the entire universe disappear?
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That was frightening.
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Did you ever find an answer to that question?
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No. Nobody's ever found an answer, but I stopped being bothered by it.
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It's kind of like
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Woody Allen in one of his films, you may recall.
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He goes to a shrink when he's a child, and the shrink asks him, what's your problem?
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He says, I just learned that the universe is expanding.
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I can't handle that.
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And then another absurd question is, what do you think is the meaning of our existence here,
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our life on earth, our brief little moment in time?
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That's something we answer by our own activities.
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There's no general answer.
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We determine what the meaning of it is.
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The action determined in meaning meaning in the sense of significance not meaning in the sense
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that chair means this you know but the significance of your life is something you create
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no thank you so much for talking today it was a huge honor thank you
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so much thanks for listening to this conversation with no chomsky
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and thank you to our presenting sponsor cash app download it use code lex podcast you'll get ten dollars
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Thank you for listening and hope to see you next time.
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Vocabolario e note di pronuncia per questa lezione
Questa lezione di conversazione si basa sul video “Noam Chomsky: Language, Cognition, and Deep Learning”. Questo video contiene 259 frasi e 4949 parole da ripetere con lo shadowing. Il parlato dura 35:37. Chi parla mantiene un ritmo costante di circa 139 parole al minuto, comodo per lo shadowing. Il 83% delle parole rientra nelle 3.000 più comuni dell’inglese; conviene studiare le altre prima di iniziare.
Vocaboli chiave di questo video
15 parole del video che vale la pena imparare, con pronuncia e significato:
| Parola | Pronuncia | Significato |
|---|---|---|
| experiment sostantivo | /ɪkˈspɛɹ.ə.mənt/ | esperimento |
| carefully avverbio | /ˈkɛɹf(ə)li/ | minuziosamente, accuratamente |
| cognitive aggettivo | /ˈkɑɡ.nɪ.tɪv/ | cognitivo |
| essentially avverbio | /ɪˈsɛnʃəli/ | in essenza |
| podcast sostantivo | /ˈpɑdˌkæst/ | podcast, audioprogramma |
| expand verbo | /ɪkˈspænd/ | estendere, espandere |
| neural aggettivo | /ˈnʊɹəl/ | neurale |
| corpus sostantivo | /ˈkɔɹpəs/ | corpus |
| organism sostantivo | /ˈɔɹ.ɡəˌnɪz.əm/ | organismo |
| endowment sostantivo | /ɛnˈdaʊmənt/ | dotazione |
| remote aggettivo | /ɹəˈməʊt̞/ | remoto |
| genetic aggettivo | /d͡ʒəˈnɛt.ɪk/ | genetico |
| mechanical aggettivo | /məˈkænəkəl/ | meccanico |
| puzzle sostantivo | /ˈpʌzəl/ | mistero, rompicapo |
| fundamental aggettivo | /ˌfʌn.dəˈmɛn.təl/ | fondamentale |
I phrasal verb che sentirai
| Parola | Pronuncia | Significato |
|---|---|---|
| carry out verbo | /ˈkæ.ɹi aʊt/ | compiere, realizzare |
| go back verbo | tornare | |
| find out verbo | scoprire | |
| point out verbo | additare | |
| set up verbo | /ˌsɛt ˈʌp/ | preparare, installare |
| take up verbo | sollevare, prendere | |
| turn out verbo | risultare |
Frasi da ripetere
Frasi brevi e complete del video che puoi riutilizzare nella conversazione di tutti i giorni:
- Do you think that's deeply linked with language?
- We can ask that question, is it useful?
- Does it tell you anything about human language?
- In general do you ponder the value of mortality?
- Do you think about your own mortality?
La grammatica di questo video
Le strutture che chi parla usa di più, con le parole esatte del video:
| Struttura | Nel video |
|---|---|
| Present perfect have/has + participio passato — un’azione passata che conta ancora adesso | has spent · has been · I've personally seen |
| Forma passiva be + participio passato — conta ciò che accade, non chi lo fa | is made · was set · was moved |
| Frasi relative who / which + frase — un’informazione in più su una persona o una cosa | organisms, which are · limits which are · guy who fixed |
Pronuncia a cui fare attenzione
Chi parla usa 64 contrazioni e forme ridotte, come can't, you're, doesn't. Pronunciale nella forma breve, così come le senti.
- I suoni “sh” e “zh”: essentially /ɪˈsɛnʃəli/, observation /ˌɑbzɚˈveɪʃn̩/, conception /kənˈsɛpʃən/, explanation /ˌɛkspləˈneɪʃən/, evolution /ˌiːvəˈluːʃ(ə)n/
- Parole lunghe — attenzione all’accento: experiment /ɪkˈspɛɹ.ə.mənt/, essentially /ɪˈsɛnʃəli/, organism /ˈɔɹ.ɡəˌnɪz.əm/, mechanical /məˈkænəkəl/, fundamental /ˌfʌn.dəˈmɛn.təl/
I suoni difficili per chi parla italiano:
- /h/ — va soffiata, non è muta: happiness /ˈhæpinɪs/, humour /ˈhjuːmɚ/
- Consonante finale — senza aggiungere una vocale dopo: experiment /ɪkˈspɛɹ.ə.mənt/, cognitive /ˈkɑɡ.nɪ.tɪv/, podcast /ˈpɑdˌkæst/, expand /ɪkˈspænd/, corpus /ˈkɔɹpəs/
- /æ/ — più aperta della “e”: podcast /ˈpɑdˌkæst/, expand /ɪkˈspænd/, mechanical /məˈkænəkəl/, mortality /mɔɹˈtælɪti/, triangle /ˈtɹaɪˌæŋɡəl/
Come esercitarsi con questo video
- Ascolta tutto il video una volta senza parlare e annota le parole che non conosci.
- Fai shadowing frase per frase a velocità normale, ripetendo ognuna finché il tuo ritmo coincide con quello di chi parla.
- Registrati e confronta con l’originale, facendo attenzione a parole come experiment, carefully, cognitive.
Cos'è la tecnica dello Shadowing?
Shadowing è una tecnica di apprendimento delle lingue supportata da studi scientifici, originariamente sviluppata per la formazione dei traduttori professionisti e resa popolare dal poliglotta Dr. Alexander Arguelles. Il metodo è semplice ma potente: ascolti un audio in inglese di madrelingua e lo ripeti immediatamente ad alta voce — come un'ombra che segue il parlante con un ritardo di solo 1–2 secondi. A differenza dell'ascolto passivo o degli esercizi di grammatica, lo shadowing costringe il tuo cervello e i muscoli della bocca a elaborare e riprodurre simultaneamente i modelli di discorso reale. La ricerca dimostra che migliora significativamente la precisione della pronuncia, l'intonazione, il ritmo, il discorso connesso, la comprensione dell'ascolto e la fluidità del parlato — rendendolo uno dei metodi più efficaci per la preparazione alla prova di speaking dell'IELTS e per la comunicazione reale in inglese.