Class: ID: Name: . L7 gap-filling test for EA 1Akand 2Af (2011/06/14)
prepared by Kow Kuroda
The story below was taken fromTED(http://www.ted.com)
1 Deb Roy: The birth of a word
Imagine if you could 1. record your life — ev- erything you said, everything you did, available in a perfect memory store at your fingertips, so you could go back and find memorable 2. moments and relive them, or sift through traces of time and discover patterns in your own life that previously had gone undiscovered. Well that’s exactly the jour- ney that my family began five and a half years ago.
This is my wife and collaborator, Rupal. And on this day, at this moment, we 3. walked into the house with our first child, our beautiful baby boy. And we walked into a house with a very special home video recording system.
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This moment and thousands of other moments special for us, were captured 4. in our home be- cause in every room in the house, if you looked up, it’s your camera and a microphone, and if you looked down, you’d get this bird’s-eye 5. view of the room. Here’s our living room, the baby bedroom, kitchen, dining room and the rest of the house. And all of these fed into a disc array that was designed for a continuous 6. capture . So here we are flying through a day in our home as we move from sunlit morning through incandescent evening and, finally, 7. lights out for the day. Over the course of three years, we recorded eight to 10 hours a day, amassing roughly a quarter-million hours of multi-track audio and video.
So you’re looking at a piece of what is by far the largest home video collection ever made. (Laughter) And what this 8. data represents for our family at a personal level, the, the, the impact has already been immense, and we’re still learning its value. Count- less moments of unsolicited natural moments, not posed 9. moments , are captured there, and we’re starting to learn how to discover them and find them.
But there’s also a scientific reason that drove this project, which was to use this kind of natural longi- tudinal data to 10. understand the process of how a child learns language — that child being my son.
And so with many privacy provisions put in place to protect everyone 11. who was recorded in the data, we made elements of the data available to my trusted research team at MIT. So we could start teas- ing apart patterns in this massive data set, trying to understand the influence of 12. social environ- ments on language acquisition. So we’re looking here at one of the first things we started to do. This is my wife and I cooking breakfast in the kitchen.
And as 13. we move through space and through time, a very everyday pattern of life in the kitchen.
In order to convert 14. this opaque, 90,000 hours of video into something that we could start to see, we use motion analysis to pull out, as we move through space and through time, what we call space- time worms. And this has become part of our toolkit for being able to 15. look and see where the activ- ities are in the data, and with it, trace the pattern of, in particular, where my son moved throughout the home, so that we could focus our transcription 1
efforts, all of the speech environment around my son — all of the 16. words that he heard from my- self, my wife, our nanny, and over time, the words he began to produce. So with that technology and that data and the ability to, with machine assistance, transcribe 17. speech , we’ve now transcribed well over seven million words of our home transcripts.
And with that, let me take you now for a first tour into the data.
So you’ve all, I’m sure, seen time-lapse videos where a flower will blossom as you accelerate time.
I’d like you to now 18. experience the blossoming of a speech form. My son, soon after his first birth- day, would say “gaga” to meanwater. And over the course of the next half-year, he slowly learned to ap- proximate the 19. proper adult form, “water.” So we’re going to cruise through half a year in about 40 seconds. No video here, so you can focus on the sound, the acoustics, of a new 20. kind of trajec- tory: “gaga” to “water.”
Baby: Gagagagagaga Gaga gaga gaga guga guga guga wada gaga gaga guga gaga wader guga guga water water water water water wa- ter water water water.
He 21. sure nailed it, didn’t he?
So he didn’t just learn water. Over the course of the 24 months, the first two years, that we re- ally focused on, this is a 22. map of every word he learned in chronological order. And because we have full transcripts, we’ve identified each of the 503 words that he learned to produce by his sec- ond birthday. He was an early 23. talker . And so we started to analyze why. Why were certain words born before others? This is one of the first results that came out of our study a little over a year ago that really surprised us. The way to inter- pret this apparently simple graph is on the vertical is an 24. indication of how complex caregiver ut- terances are based on the length of utterances. And the vertical axis is time.
And all of the data, we aligned based on the, the following idea: Every 25. time my son would learn a word, we would trace back and look at all of the language he heard that contained that word.
And we would plot the relative 26. length of the utterances. And what we found was this curious phenomena, that caregiver speech would systemati- cally dip to a minimum, making language as sim- ple as possible, and then slowly ascend back up in complexity. And the amazing thing was that 27. bounce , that dip, lined up almost precisely with when each word was born — word after word, systematically. So it appears that all three primary caregivers — myself, my wife and our nanny — were systematically and, I would think, subcon- sciously restructuring our 28. language to meet him at the moment of, the birth of a word and bring him gently into more complex language. And the implications of this — there are many, but one I just want to point out, is 29. that there must be amaz- ing feedback loops. It’s not, of course, my son is learning from his linguistic environment, but the en- vironment is learning from him. That environment, people, are in these tight 30. feedback loops and creating a kind of scaffolding that has not been no- ticed until now.
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