TED2013
Ajit Narayanan: A word game to communicate in any language
Adžit Narajanan (Ajit Narayanan): Igra rečima za komunikaciju na bilo kom jeziku
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Dok je radio sa decom koja imaju poteškoće sa govorom, Adžit Narajanan skicirao je način da se o jeziku razmišlja u slikama, da se slike i pojmovi povezuju u "mape". Ova ideja sada stoji iza aplikacije koja pomaže nemima da komuniciraju, a velika ideja iza svega toga, konceptualni jezik zvani FreeSpeech, ima uzbudljiv potencijal.
Ajit Narayanan - Visual grammar engine inventor
Ajit Narayanan is the inventor of Avaz, an affordable, tablet-based communication device for people who are speech-impaired. Full bio
Ajit Narayanan is the inventor of Avaz, an affordable, tablet-based communication device for people who are speech-impaired. Full bio
Double-click the English transcript below to play the video.
00:12
I work with children with autism.
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Ja radim sa decom sa autizmom.
00:15
Specifically, I make technologies
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Tačnije, razvijam tehnologije
00:17
to help them communicate.
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koje im pomažu da komuniciraju.
00:19
Now, many of the problems that children
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Mnogi problemi sa kojima se deca
00:21
with autism face, they have a common source,
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sa autizmom suočavaju,
imaju isti izvor,
imaju isti izvor,
00:24
and that source is that they find it difficult
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a to je da im je veoma teško
00:26
to understand abstraction, symbolism.
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da razumeju apstrakciju, simbolizam.
00:32
And because of this, they have
a lot of difficulty with language.
a lot of difficulty with language.
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Zbog ovoga, ona imaju
mnogo poteškoća sa jezikom.
mnogo poteškoća sa jezikom.
00:36
Let me tell you a little bit about why this is.
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Dozvolite mi da vam kažem
malo o tome zašto je to tako.
malo o tome zašto je to tako.
00:39
You see that this is a picture of a bowl of soup.
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Ovo je slika činije sa supom.
00:43
All of us can see it. All of us understand this.
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Svi mi to vidimo.
Svi mi razumemo to.
Svi mi razumemo to.
00:46
These are two other pictures of soup,
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Ovo su dve druge slike supe,
00:48
but you can see that these are more abstract
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ali su one apstraktnije.
00:50
These are not quite as concrete.
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Nisu u tolikoj meri konkretne.
00:52
And when you get to language,
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A kada stignemo do jezika,
00:54
you see that it becomes a word
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vidimo da ona postaje reč,
00:56
whose look, the way it looks and the way it sounds,
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čiji izgled, kako izgleda i kako zvuči,
00:59
has absolutely nothing to do
with what it started with,
with what it started with,
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nema nikakve veze
sa onim od čega je potekla
sa onim od čega je potekla
01:02
or what it represents, which is the bowl of soup.
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ili sa onim što predstavlja,
a to je činija supe.
a to je činija supe.
01:05
So it's essentially a completely abstract,
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Ona je u suštini
u potpunosti apstraktna,
u potpunosti apstraktna,
01:08
a completely arbitrary representation of something
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potpuno arbitrarna reprezentacija nečega
01:10
which is in the real world,
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što je u stvarnom svetu
01:12
and this is something that children with autism
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i to je nešto sa čime
deca sa autizmom
deca sa autizmom
01:13
have an incredible amount of difficulty with.
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imaju neverovatnih poteškoća.
01:17
Now that's why most of the people
that work with children with autism --
that work with children with autism --
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Zbog ovoga većina ljudi
koji rade sa decom sa autizmom -
koji rade sa decom sa autizmom -
01:19
speech therapists, educators --
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govorni terapeuti, učitelji -
01:21
what they do is, they try to help children with autism
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pokušavaju da pomognu
deci sa autizmom
deci sa autizmom
01:24
communicate not with words, but with pictures.
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da komuniciraju,
ne rečima, nego putem slika.
ne rečima, nego putem slika.
01:27
So if a child with autism wanted to say,
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Ako bi dete sa autizmom
želelo da kaže:
želelo da kaže:
01:29
"I want soup," that child would pick
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"Želim supu",
to dete bi izabralo
to dete bi izabralo
01:31
three different pictures, "I," "want," and "soup,"
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tri različite slike:
"ja", "želeti" i "supa"
"ja", "želeti" i "supa"
01:34
and they would put these together,
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i spojilo bi ih
01:35
and then the therapist or the parent would
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i tako bi terapeut ili roditelj razumeo
01:37
understand that this is what the kid wants to say.
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da je to ono što dete želi da kaže.
01:39
And this has been incredibly effective;
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Ovo je bilo izuzetno efikasno;
01:41
for the last 30, 40 years
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ljudi su radili ovo
01:43
people have been doing this.
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u proteklih 30, 40 godina.
01:45
In fact, a few years back,
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U stvari, pre nekoliko godina,
01:46
I developed an app for the iPad
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razvio sam aplikaciju za Ajped
01:49
which does exactly this. It's called Avaz,
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koja radi upravo ovo.
Ona se zove Avaz,
a radi tako što dete bira
a radi tako što dete bira
01:51
and the way it works is that kids select
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01:53
different pictures.
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različite slike.
01:55
These pictures are sequenced
together to form sentences,
together to form sentences,
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Ove slike su poređane
u nizu i stvaraju rečenice,
u nizu i stvaraju rečenice,
01:57
and these sentences are spoken out.
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a onda se ove rečenice izgovaraju.
01:59
So Avaz is essentially converting pictures,
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Avaz u suštini radi konverziju,
02:02
it's a translator, it converts pictures into speech.
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on je prevodilac
koji pretvara slike u govor.
koji pretvara slike u govor.
02:06
Now, this was very effective.
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Ovo je bilo veoma efikasno.
02:07
There are thousands of children using this,
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Hiljade dece koristi ovo,
02:09
you know, all over the world,
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znate, širom sveta,
02:10
and I started thinking about
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i počeo sam da razmišljam
02:12
what it does and what it doesn't do.
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o tome šta ono radi, a šta ne radi.
02:15
And I realized something interesting:
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I shvatio sam nešto interesantno:
02:17
Avaz helps children with autism learn words.
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Avaz pomaže deci sa autizmom
da nauče reči.
da nauče reči.
02:21
What it doesn't help them do is to learn
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Ali ne pomaže im da nauče
02:23
word patterns.
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obrasce tih reči.
02:26
Let me explain this in a little more detail.
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Dozvolite mi da objasnim ovo
malo detaljnije.
malo detaljnije.
02:29
Take this sentence: "I want soup tonight."
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Uzmimo rečenicu:
"Želim supu večeras."
"Želim supu večeras."
02:32
Now it's not just the words
here that convey the meaning.
here that convey the meaning.
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Nisu samo reči te
koje prenose značenje.
koje prenose značenje.
02:36
It's also the way in which these words are arranged,
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Tu je i način na koji
su te reči poređane,
su te reči poređane,
02:39
the way these words are modified and arranged.
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način na koji su one
izmenjene i poređane.
izmenjene i poređane.
02:41
And that's why a sentence like "I want soup tonight"
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Zato je rečenica:
"Želim supu večeras."
"Želim supu večeras."
02:44
is different from a sentence like
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drugačija od rečenice kao što je:
02:46
"Soup want I tonight," which
is completely meaningless.
is completely meaningless.
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"Supa želeti ja večeras",
koja je u potpunosti besmislena.
koja je u potpunosti besmislena.
02:49
So there is another hidden abstraction here
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Tu postoji još jedna
skrivena apstrakcija
skrivena apstrakcija
02:52
which children with autism find
a lot of difficulty coping with,
a lot of difficulty coping with,
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sa kojom se
deca sa autizmom teško nose,
deca sa autizmom teško nose,
02:55
and that's the fact that you can modify words
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a to je činjenica da reči
možemo da izmenimo
možemo da izmenimo
02:58
and you can arrange them to have
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i možemo da ih poređamo tako
03:00
different meanings, to convey different ideas.
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da dobijemo različita značenja,
prenesemo različite ideje.
prenesemo različite ideje.
03:03
Now, this is what we call grammar.
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To je ono što zovemo gramatikom.
03:07
And grammar is incredibly powerful,
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Gramatika je izuzetno moćna,
03:09
because grammar is this one component of language
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jer je gramatika komponenta jezika
03:12
which takes this finite vocabulary that all of us have
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koja uzima ograničen vokabular
koji svi mi imamo
koji svi mi imamo
03:15
and allows us to convey an
infinite amount of information,
infinite amount of information,
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i dozvoljava nam da prenesemo
neograničenu količinu informacija,
neograničenu količinu informacija,
03:20
an infinite amount of ideas.
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beskrajni broj ideja.
03:22
It's the way in which you can put things together
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To je način na koji spajamo stvari
03:24
in order to convey anything you want to.
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kako bismo preneli
šta god želimo.
šta god želimo.
03:26
And so after I developed Avaz,
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Nakon što sam razvio Avaz,
03:28
I worried for a very long time
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dugo sam razmišljao
03:30
about how I could give grammar
to children with autism.
to children with autism.
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o tome kako deci sa autizmom
da pružim gramatiku.
da pružim gramatiku.
03:34
The solution came to me from
a very interesting perspective.
a very interesting perspective.
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Rešenje mi se javilo
iz jednog interesantnog ugla.
iz jednog interesantnog ugla.
03:36
I happened to chance upon a child with autism
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Sreo sam jedno dete sa autizmom
03:39
conversing with her mom,
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koje je razgovaralo sa svojom majkom
03:41
and this is what happened.
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i ovo se desilo.
03:44
Completely out of the blue, very spontaneously,
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Sasvim neočekivano, veoma spontano
03:46
the child got up and said, "Eat."
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dete je prišlo i reklo: "Jesti."
03:48
Now what was interesting was
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Ono što je bilo interesantno
03:50
the way in which the mom was trying to tease out
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je bio način na koji je majka
pokušavala da odgonetne
pokušavala da odgonetne
03:54
the meaning of what the child wanted to say
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značenje onoga
što je dete želelo da kaže
što je dete želelo da kaže
03:56
by talking to her in questions.
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postavljanjem pitanja.
03:59
So she asked, "Eat what? Do
you want to eat ice cream?
you want to eat ice cream?
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Pitala je: "Jesti šta?
Želiš li da jedeš sladoled?"
Želiš li da jedeš sladoled?"
04:01
You want to eat? Somebody else wants to eat?
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Ti želiš da jedeš?
Neko drugi želi da jede?
Neko drugi želi da jede?
04:03
You want to eat cream now? You
want to eat ice cream in the evening?"
want to eat ice cream in the evening?"
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Želiš da jedeš sladoled sada?
Želiš da jedeš sladoled uveče?"
Želiš da jedeš sladoled uveče?"
04:07
And then it struck me that
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I onda sam shvatio
04:08
what the mother had done was something incredible.
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da je majka uradila
nešto zaista neverovatno.
nešto zaista neverovatno.
04:10
She had been able to get that child to communicate
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Ona je navela to dete
da joj prenese
da joj prenese
04:12
an idea to her without grammar.
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ideju bez gramatike.
04:16
And it struck me that maybe this is what
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I onda sam shvatio da je možda ovo
04:19
I was looking for.
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ono što sam tražio.
04:20
Instead of arranging words in an order, in sequence,
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Umesto ređanja reči u nizove,
04:25
as a sentence, you arrange them
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kao rečenice, poređajmo ih
04:27
in this map, where they're all linked together
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na ovu mapu,
gde su sve one povezane
gde su sve one povezane
04:31
not by placing them one after the other
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ne putem njihovog
nizanja jednih nakon drugih,
nizanja jednih nakon drugih,
04:33
but in questions, in question-answer pairs.
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već pitanjima,
u parovima pitanja i odgovora.
u parovima pitanja i odgovora.
04:36
And so if you do this, then what you're conveying
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Ako uradimo ovo,
onda ne prenosimo
onda ne prenosimo
04:38
is not a sentence in English,
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rečenicu na engleskom,
04:40
but what you're conveying is really a meaning,
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ono što prenosimo
je u stvari značenje,
je u stvari značenje,
04:43
the meaning of a sentence in English.
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značenje rečenice na engleskom.
04:45
Now, meaning is really the underbelly,
in some sense, of language.
in some sense, of language.
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Značenje je u stvari
u nekom smislu potpora jezika.
u nekom smislu potpora jezika.
04:48
It's what comes after thought but before language.
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To je ono što dolazi
nakon misli, ali pre jezika.
nakon misli, ali pre jezika.
04:52
And the idea was that this particular representation
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Ideja je bila
da ovaj način predstavljanja
da ovaj način predstavljanja
04:54
might convey meaning in its raw form.
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može da prenese značenje
u njegovom sirovom obliku.
u njegovom sirovom obliku.
04:57
So I was very excited by this, you know,
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Bio sam veoma uzbuđen ovim, znate,
04:59
hopping around all over the place,
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skakao sam gore-dole
05:01
trying to figure out if I can convert
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pokušavajući da otkrijem
mogu li da pretvorim
mogu li da pretvorim
05:02
all possible sentences that I hear into this.
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sve moguće rečenice koje čujem u ovo.
05:05
And I found that this is not enough.
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I otkrio sam da ovo nije dovoljno.
05:07
Why is this not enough?
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Zašto nije dovoljno?
05:08
This is not enough because if you wanted to convey
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Nije dovoljno, jer ako želite
05:10
something like negation,
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da prenesete nešto kao negaciju,
05:12
you want to say, "I don't want soup,"
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želite da kažete:
"Ne želim supu",
"Ne želim supu",
05:14
then you can't do that by asking a question.
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onda to ne možete da uradite
postavljanjem pitanja.
postavljanjem pitanja.
05:16
You do that by changing the word "want."
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To radite promenom reči "želeti".
05:18
Again, if you wanted to say,
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Ukoliko bismo želeli da kažemo:
05:20
"I wanted soup yesterday,"
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"Želeo sam supu juče",
05:22
you do that by converting
the word "want" into "wanted."
the word "want" into "wanted."
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pretvaramo reč "želeti" u "želeo".
05:25
It's a past tense.
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To je prošlo vreme.
05:26
So this is a flourish which I added
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Ovo je ono što sam dodao
05:28
to make the system complete.
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kako bih kompletirao sistem.
05:30
This is a map of words joined together
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Ovo je mapa povezanih reči
05:32
as questions and answers,
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putem pitanja i odgovora,
05:34
and with these filters applied on top of them
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a ovo su filteri primenjeni na njima
05:36
in order to modify them to represent
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kako bi pretvorili reči da bi one
05:38
certain nuances.
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predstavljale određene nijanse.
05:39
Let me show you this with a different example.
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Pogledajmo to na drugačijem primeru.
05:41
Let's take this sentence:
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Uzmimo rečenicu:
05:43
"I told the carpenter I could not pay him."
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"Rekao sam stolaru
da ne mogu da mu platim."
da ne mogu da mu platim."
05:45
It's a fairly complicated sentence.
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Ovo je poprilično složena rečenica.
05:46
The way that this particular system works,
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Način na koji ovaj sistem radi je takav
05:48
you can start with any part of this sentence.
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da možete da krenete
od bilo kog dela ove rečenice.
od bilo kog dela ove rečenice.
05:51
I'm going to start with the word "tell."
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Ja ću krenuti sa rečju: "reći".
05:53
So this is the word "tell."
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Ovo je reč "reći".
05:54
Now this happened in the past,
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Pošto se ovo desilo u prošlosti,
05:56
so I'm going to make that "told."
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pretvoriću je u "rekao".
05:58
Now, what I'm going to do is,
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Sada ću
06:00
I'm going to ask questions.
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postaviti pitanje.
06:01
So, who told? I told.
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Ko je rekao? Ja sam rekao.
06:04
I told whom? I told the carpenter.
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Kome sam rekao? Rekao sam stolaru.
06:06
Now we start with a different part of the sentence.
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Sada ćemo krenuti
od drugog dela rečenice.
od drugog dela rečenice.
06:07
We start with the word "pay,"
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Krenućemo od reči "platiti"
06:09
and we add the ability filter to it to make it "can pay."
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i dodaćemo filter za mogućnost
da bismo je pretvorili u "mogu da platim".
da bismo je pretvorili u "mogu da platim".
Zatim ćemo je pretvoriti u
"ne mogu da platim"
"ne mogu da platim"
06:14
Then we make it "can't pay,"
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06:16
and we can make it "couldn't pay"
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i onda u "nisam mogao da platim"
06:18
by making it the past tense.
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dodavajući prošlo vreme.
Ko nije mogao da plati?
Ja nisam mogao da platim.
Ja nisam mogao da platim.
06:19
So who couldn't pay? I couldn't pay.
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06:21
Couldn't pay whom? I couldn't pay the carpenter.
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Kome nisam mogao da platim?
Nisam mogao da platim stolaru.
Nisam mogao da platim stolaru.
06:24
And then you join these two together
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Onda spojimo ova dva dela
06:25
by asking this question:
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postavljanjem pitanja:
06:27
What did I tell the carpenter?
157
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1737
"Šta sam rekao stolaru?
06:29
I told the carpenter I could not pay him.
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Rekao sam stolaru
da ne mogu da mu platim.
da ne mogu da mu platim.
06:33
Now think about this. This is
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1937
Razmislite o ovome. Ovo je
06:35
—(Applause)—
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- (Aplauz) -
06:38
this is a representation of this sentence
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ovo je predstavljanje ove rečenice
bez jezika.
bez jezika.
06:42
without language.
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06:44
And there are two or three
interesting things about this.
interesting things about this.
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Postoje dve ili tri
interesantne stvari u vezi s ovim.
interesantne stvari u vezi s ovim.
06:46
First of all, I could have started anywhere.
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Prvo, mogao sam da počnem bilo gde.
06:50
I didn't have to start with the word "tell."
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Nisam morao da krenem sa rečju "reći".
06:52
I could have started anywhere in the sentence,
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Mogao sam da krenem bilo gde
06:53
and I could have made this entire thing.
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i mogao sam da stvorim sve ovo.
06:55
The second thing is, if I wasn't an English speaker,
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Druga stvar je,
da nisam govornik engleskog,
da nisam govornik engleskog,
06:57
if I was speaking in some other language,
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da govorim nekim drugim jezikom,
07:00
this map would actually hold true in any language.
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ova mapa bi bila identična
u bilo kom jeziku.
u bilo kom jeziku.
07:03
So long as the questions are standardized,
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1990
Dokle god su pitanja standardizovana,
07:05
the map is actually independent of language.
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4287
ova mapa je u stvari nezavisna od jezika.
07:09
So I call this FreeSpeech,
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Ovo sam nazvao FreeSpeech
07:11
and I was playing with this for many, many months.
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2935
i igrao sam se ovime mnogo meseci.
07:14
I was trying out so many
different combinations of this.
different combinations of this.
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2726
Pokušavao sam mnogo različitih kombinacija
07:17
And then I noticed something very
interesting about FreeSpeech.
interesting about FreeSpeech.
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I onda sam primetio
nešto veoma interesantno.
nešto veoma interesantno.
07:19
I was trying to convert language,
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Pokušavao sam da pretvorim jezik,
07:22
convert sentences in English
into sentences in FreeSpeech,
into sentences in FreeSpeech,
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2384
rečenice na engleskom
u rečenice FreeSpeech-a
u rečenice FreeSpeech-a
07:25
and vice versa, and back and forth.
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i obrnuto, u jednom i drugom pravcu.
07:27
And I realized that this particular configuration,
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2255
I shvatio sam da mi je ova konfiguracija,
07:29
this particular way of representing language,
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2026
ovaj način predstavljanja jezika,
07:31
it allowed me to actually create very concise rules
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da su mi dozvolili da stvorim
veoma koncizna pravila
veoma koncizna pravila
07:35
that go between FreeSpeech on one side
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2734
koja povezuju FreeSpeech sa jedne strane
07:38
and English on the other.
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1488
i engleski s druge.
07:39
So I could actually write this set of rules
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Tako bih mogao na napišem
set ovakvih pravila
set ovakvih pravila
07:42
that translates from this particular
representation into English.
representation into English.
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koji prevodi iz ove
reprezentacije u engleski.
reprezentacije u engleski.
07:45
And so I developed this thing.
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1831
I razvio sam to.
07:47
I developed this thing called
the FreeSpeech Engine
the FreeSpeech Engine
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Razvio sam takozvani FreeSpeech Engine
07:49
which takes any FreeSpeech sentence as the input
189
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2561
koji uzima bilo koju FreeSpeech
rečenicu kao ulaznu informaciju
rečenicu kao ulaznu informaciju
07:52
and gives out perfectly grammatical English text.
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i daje gramatičnu englesku rečenicu.
07:56
And by putting these two pieces together,
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1605
Spajanjem ova dva dela
07:57
the representation and the engine,
192
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1881
predstave i mehanizma
07:59
I was able to create an app, a
technology for children with autism,
technology for children with autism,
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3796
stvorio sam aplikaciju,
tehnologiju za decu sa autizmom
tehnologiju za decu sa autizmom
08:03
that not only gives them words
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2499
koja im ne daje samo reči
08:05
but also gives them grammar.
195
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3941
nego im daje i gramatiku.
08:09
So I tried this out with kids with autism,
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2360
Ispobao sam ovo sa decom sa autizmom
08:12
and I found that there was an
incredible amount of identification.
incredible amount of identification.
197
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5013
i otkrio sam da postoji
visok stepen identifikacije.
visok stepen identifikacije.
08:17
They were able to create sentences in FreeSpeech
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2720
Mogli su da stvaraju rečenice
u FreeSpeech-u
u FreeSpeech-u
08:19
which were much more complicated
but much more effective
but much more effective
199
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2558
koje su bile mnogo složenije,
ali i efikasnije
ali i efikasnije
08:22
than equivalent sentences in English,
200
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2899
od ekvivalenata na engleskom
08:25
and I started thinking about
201
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1682
i počeo sam da razmišljam o tome
08:27
why that might be the case.
202
495015
1969
zašto je to tako.
08:28
And I had an idea, and I want to
talk to you about this idea next.
talk to you about this idea next.
203
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4287
Imao sam ideju, i želim sada
da vam pričam o njoj.
da vam pričam o njoj.
08:33
In about 1997, about 15 years back,
204
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3142
1997, pre oko 15 godina
08:36
there were a group of scientists that were trying
205
504413
2011
grupa naučnika pokušavala je
08:38
to understand how the brain processes language,
206
506424
2389
da razume kako mozak obrađuje jezik
i otkrili su nešto veoma interesantno.
08:40
and they found something very interesting.
207
508813
1779
08:42
They found that when you learn a language
208
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1872
Otkrili su da kada učimo jezik
08:44
as a child, as a two-year-old,
209
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2912
kao deca, kao dvogodišnjaci,
08:47
you learn it with a certain part of your brain,
210
515376
2366
učimo ga sa jednim delom mozga,
08:49
and when you learn a language as an adult --
211
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1600
a kada ga učimo kao odrasli -
08:51
for example, if I wanted to
learn Japanese right now —
learn Japanese right now —
212
519342
3911
na primer, ako bih sada
želeo da naučim japanski -
želeo da naučim japanski -
08:55
a completely different part of my brain is used.
213
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2707
koristio bih potpuno drugačiji deo mozga.
08:57
Now I don't know why that's the case,
214
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1831
Ne znam zašto je to tako,
08:59
but my guess is that that's because
215
527791
1991
pretpostavljam da je to zato što
09:01
when you learn a language as an adult,
216
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2437
kada učimo jezike kao odrasli,
09:04
you almost invariably learn it
217
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1616
skoro stalno ih učimo
09:05
through your native language, or
through your first language.
through your first language.
218
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4266
putem maternjeg jezika
ili putem prvog jezika.
ili putem prvog jezika.
09:10
So what's interesting about FreeSpeech
219
538101
3252
Ono što je interesantno
u vezi FreeSpeech-a
u vezi FreeSpeech-a
09:13
is that when you create a sentence
220
541353
1802
je da kada stvarate rečenicu
09:15
or when you create language,
221
543155
1695
ili kada stvarate jezik,
09:16
a child with autism creates
language with FreeSpeech,
language with FreeSpeech,
222
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3070
kada dete sa autizmom
stvara jezik pomoću FreeSpeech-a,
stvara jezik pomoću FreeSpeech-a,
09:19
they're not using this support language,
223
547920
1833
ono ga ne koristi kao pomoćni jezik,
09:21
they're not using this bridge language.
224
549753
2211
kao vezu između dva jezika.
09:23
They're directly constructing the sentence.
225
551964
2657
Oni direktno stvaraju rečenicu.
09:26
And so this gave me this idea.
226
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2193
Ovo mi je dalo ideju.
09:28
Is it possible to use FreeSpeech
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2024
Da li je moguće koristiti FreeSpeech
09:30
not for children with autism
228
558838
2510
ne za decu sa autizmom,
09:33
but to teach language to people without disabilities?
229
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6262
nego da ljude bez invaliditeta
učimo jezicima?
učimo jezicima?
09:39
And so I tried a number of experiments.
230
567610
1978
Sproveo sam nekoliko eksperimenata.
09:41
The first thing I did was I built a jigsaw puzzle
231
569588
2948
Prva stvar koju sam napravio je slagalica
09:44
in which these questions and answers
232
572536
1970
u kojoj su ova pitanja i odgovori
09:46
are coded in the form of shapes,
233
574506
1835
pretvoreni u oblike,
09:48
in the form of colors,
234
576341
1138
boje
09:49
and you have people putting these together
235
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1849
i ljudi ovo slažu
09:51
and trying to understand how this works.
236
579328
1773
i pokušavaju da razumeju kako radi.
09:53
And I built an app out of it, a game out of it,
237
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2376
Napravio sam aplikaciju, igru,
09:55
in which children can play with words
238
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2661
u kojoj deca mogu da se igraju rečima,
09:58
and with a reinforcement,
239
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1704
i putem potvrde,
09:59
a sound reinforcement of visual structures,
240
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2585
zvučne potvrde vizuelnih struktura,
10:02
they're able to learn language.
241
590427
2013
oni mogu da nauče jezik.
10:04
And this, this has a lot of potential, a lot of promise,
242
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2736
Ovo ima mnogo potencijala, obećava mnogo
10:07
and the government of India recently
243
595176
1975
i vlada Indije je nedavno
10:09
licensed this technology from us,
244
597151
1404
otkupila ovu tehnologiju od nas
10:10
and they're going to try it out
with millions of different children
with millions of different children
245
598555
2074
i isprobavaju je sa milionima dece
10:12
trying to teach them English.
246
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2605
pokušavajući da ih nauče engleski.
10:15
And the dream, the hope, the vision, really,
247
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2614
San, nada, vizija
10:17
is that when they learn English this way,
248
605848
3082
je da kada ovako uče engleski
10:20
they learn it with the same proficiency
249
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2643
oni ga uče sa istom sposobnošću
10:23
as their mother tongue.
250
611573
3718
kao svoj maternji jezik.
10:27
All right, let's talk about something else.
251
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3816
Hajde da govorimo o nečemu drugom.
10:31
Let's talk about speech.
252
619107
1997
Hajde da govorimo o govoru.
10:33
This is speech.
253
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1271
Ovo je govor.
10:34
So speech is the primary mode of communication
254
622375
1962
Govor je primarno sredstvo komunikacije
10:36
delivered between all of us.
255
624337
1613
između svih nas.
10:37
Now what's interesting about speech is that
256
625950
1855
Kod govora je interesantno to što je on
10:39
speech is one-dimensional.
257
627805
1245
jednodimenzionalan.
10:41
Why is it one-dimensional?
258
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1359
Zašto je jednodimenzionalan?
10:42
It's one-dimensional because it's sound.
259
630409
1568
Zato što je zvuk.
10:43
It's also one-dimensional because
260
631977
1539
Jednodimenzionalan je takođe
10:45
our mouths are built that way.
261
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1205
jer su nam usta tako napravljena.
10:46
Our mouths are built to create
one-dimensional sound.
one-dimensional sound.
262
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3512
Naša usta su stvorena
da stvaraju jednodimenzionalni zvuk.
da stvaraju jednodimenzionalni zvuk.
10:50
But if you think about the brain,
263
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2866
Ali ako razmislite, mozak,
10:53
the thoughts that we have in our heads
264
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1764
misli koje imamo u glavi,
10:54
are not one-dimensional.
265
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2102
nisu jednodimenzionalne.
10:56
I mean, we have these rich,
266
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1459
Imamo ove bogate,
10:58
complicated, multi-dimensional ideas.
267
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3028
komplikovane, multi-dimenzionalne ideje.
11:01
Now, it seems to me that language
268
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1690
Čini mi se da je jezik
11:03
is really the brain's invention
269
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2332
u stvari izum mozga
11:05
to convert this rich, multi-dimensional thought
270
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3096
kojim pretvara ovu bogatu,
multi-dimenzionalnu misao
multi-dimenzionalnu misao
11:08
on one hand
271
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1587
s jedne strane
11:10
into speech on the other hand.
272
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1923
u govor s druge strane.
11:12
Now what's interesting is that
273
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1762
Interesantno je to da
11:13
we do a lot of work in information nowadays,
274
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2568
danas mnogo radimo sa informacijama
11:16
and almost all of that is done
in the language domain.
in the language domain.
275
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3079
i skoro sve što se radi
je u domenu jezika.
je u domenu jezika.
11:19
Take Google, for example.
276
667489
1939
Uzmimo Gugl, na primer.
11:21
Google trawls all these
countless billions of websites,
countless billions of websites,
277
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2677
Gugl pročešljava
nebrojene milijarde sajtova,
nebrojene milijarde sajtova,
11:24
all of which are in English,
and when you want to use Google,
and when you want to use Google,
278
672105
2725
od kojih su svi na engleskom,
i kada želite da koristite Gugl,
i kada želite da koristite Gugl,
11:26
you go into Google search, and you type in English,
279
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2450
idete na Gugl pretragu
i kucate na engleskom,
i kucate na engleskom,
11:29
and it matches the English with the English.
280
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4163
i ona upari engleski s engleskim.
11:33
What if we could do this in FreeSpeech instead?
281
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3583
Šta ako bismo ovo mogli
da uradimo sa FreeSpeech-om?
da uradimo sa FreeSpeech-om?
11:37
I have a suspicion that if we did this,
282
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2301
Čini mi se da kada bismo ovo uradili,
11:39
we'd find that algorithms like searching,
283
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2068
otkrili bismo da su algoritmi
poput pretrage,
poput pretrage,
11:41
like retrieval, all of these things,
284
689395
2325
davanja rezultata, sve ove stvari,
11:43
are much simpler and also more effective,
285
691720
3075
da je sve to jednostavnije i efikasnije,
11:46
because they don't process
the data structure of speech.
the data structure of speech.
286
694795
4417
jer ne mora da se obradi
struktura podataka govora.
struktura podataka govora.
11:51
Instead they're processing
the data structure of thought.
the data structure of thought.
287
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5976
Umesto toga se obrađuje
struktura podataka misli.
struktura podataka misli.
11:57
The data structure of thought.
288
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2808
Struktura podataka misli.
11:59
That's a provocative idea.
289
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2076
To je provokativna zamisao.
12:02
But let's look at this in a little more detail.
290
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2142
Ali hajde da detaljnije pogledamo ovo.
12:04
So this is the FreeSpeech ecosystem.
291
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2366
Ovo je ekosistem FreeSpeech-a.
12:06
We have the Free Speech
representation on one side,
representation on one side,
292
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2884
Sa jedne strane imamo
prikaz FreeSpeech-a,
prikaz FreeSpeech-a,
12:09
and we have the FreeSpeech
Engine, which generates English.
Engine, which generates English.
293
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2228
i imamo mehanizam FreeSpeech-a,
koji stvara engleski.
koji stvara engleski.
12:11
Now if you think about it,
294
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1725
Ako razmislite o tome,
12:13
FreeSpeech, I told you, is completely
language-independent.
language-independent.
295
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2544
rekao sam vam da je FreeSpeech
potpuno nezavisan od jezika.
potpuno nezavisan od jezika.
12:15
It doesn't have any specific information in it
296
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2087
U sebi ne sadrži posebne informacije
12:18
which is about English.
297
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1228
vezane za engleski.
12:19
So everything that this system knows about English
298
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2800
Sve što ovaj sistem zna o engleskom
12:22
is actually encoded into the engine.
299
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4620
je zapravo zapisano u mehanizmu.
12:26
That's a pretty interesting concept in itself.
300
734698
2237
To je samo po sebi zanimljiv koncept.
12:28
You've encoded an entire human language
301
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3604
Kodirali smo čitav ljudski jezik
12:32
into a software program.
302
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2645
u softverski program.
12:35
But if you look at what's inside the engine,
303
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2531
Ali ako pogledate unutar mehanizma,
12:37
it's actually not very complicated.
304
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2358
zapravo nije veoma komplikovano.
12:40
It's not very complicated code.
305
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2105
Kod nije veoma komplikovan.
12:42
And what's more interesting is the fact that
306
750178
2672
A interesantnija je činjenica
12:44
the vast majority of the code in that engine
307
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2203
da je većina koda u tom mehanizmu
12:47
is not really English-specific.
308
755053
2412
nevezana za engleski.
12:49
And that gives this interesting idea.
309
757465
1895
To nam je dalo zanimljivu ideju.
12:51
It might be very easy for us to actually
310
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2038
Možda bi bilo lako da zapravo
12:53
create these engines in many,
many different languages,
many different languages,
311
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3826
napravimo ove mehanizme
u mnogo različitih jezika,
u mnogo različitih jezika,
12:57
in Hindi, in French, in German, in Swahili.
312
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6354
indijskom, francuskom,
nemačkom, svahiliju.
nemačkom, svahiliju.
13:03
And that gives another interesting idea.
313
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2799
A to nam je dalo još jednu
zanimljivu ideju.
zanimljivu ideju.
13:06
For example, supposing I was a writer,
314
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2654
Na primer, recimo da sam pisac,
13:09
say, for a newspaper or for a magazine.
315
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2122
za novine ili magazin.
13:11
I could create content in one language, FreeSpeech,
316
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5011
Mogao bih da stvaram sadržaj
u jednom jeziku, FreeSpeech-u,
u jednom jeziku, FreeSpeech-u,
13:16
and the person who's consuming that content,
317
784164
2056
a osoba koja konzumira taj sadržaj,
13:18
the person who's reading that particular information
318
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3061
koja čita te informacije,
13:21
could choose any engine,
319
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2495
mogla bi da odabere bilo koji mehanizam,
13:23
and they could read it in their own mother tongue,
320
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2736
i mogla bi da čita to
13:26
in their native language.
321
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3939
na svom maternjem jeziku.
13:30
I mean, this is an incredibly attractive idea,
322
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2722
Ovo je neverovatno privlačna ideja,
13:33
especially for India.
323
801173
1999
naročito za Indiju.
13:35
We have so many different languages.
324
803172
1690
Imamo toliko različitih jezika.
13:36
There's a song about India, and there's a description
325
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2142
Postoji pesma o Indiji, i postoji
13:39
of the country as, it says,
326
807004
2344
opis zemlje koji kaže,
13:41
(in Sanskrit).
327
809348
2360
(na Sanskritu).
13:43
That means "ever-smiling speaker
328
811708
2773
To znači: "govornik predivnih jezika
13:46
of beautiful languages."
329
814481
4519
koji se stalno smeje".
13:51
Language is beautiful.
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Jezik je predivan.
13:52
I think it's the most beautiful of human creations.
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Mislim da je to najlepša
od svih ljudskih kreacija.
od svih ljudskih kreacija.
13:55
I think it's the loveliest thing
that our brains have invented.
that our brains have invented.
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Mislim da je to najdraža stvar
koju su smislili naši mozgovi.
koju su smislili naši mozgovi.
13:59
It entertains, it educates, it enlightens,
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On zabavlja, obrazuje, prosvetljuje,
14:02
but what I like the most about language
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ali kod jezika najviše volim to
14:05
is that it empowers.
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što daje moć.
14:06
I want to leave you with this.
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Želim da vas ostavim sa ovim.
14:08
This is a photograph of my collaborators,
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Ovo je fotografija mojih saradnika,
najranijih saradnika,
14:10
my earliest collaborators
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14:11
when I started working on language
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kada sam počeo da radim na jeziku
14:13
and autism and various other things.
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i autizmu i drugim stvarima.
14:14
The girl's name is Pavna,
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Ime ove devojčice je Pavna,
14:16
and that's her mother, Kalpana.
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a to je njena majka, Kalpana.
14:18
And Pavna's an entrepreneur,
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Pavna je preduzetnica,
14:20
but her story is much more remarkable than mine,
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ali njena priča je fascinantnija od moje,
14:22
because Pavna is about 23.
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jer Pavna ima oko 23 godine.
14:24
She has quadriplegic cerebral palsy,
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Ona ima cerebralnu paralizu,
14:27
so ever since she was born,
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tako da od svog rođenja
14:29
she could neither move nor talk.
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nije mogla da se pomera ili priča.
14:32
And everything that she's accomplished so far,
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Sve što je do sada postigla,
14:35
finishing school, going to college,
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završavanje škole, odlazak na fakultet,
14:37
starting a company,
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osnivanje kompanije,
14:38
collaborating with me to develop Avaz,
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saradnja sa mnom na razvijanju Avaza,
14:40
all of these things she's done
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sve ove stvari je uradila
14:42
with nothing more than moving her eyes.
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samo uz pomeranje svojih očiju.
14:48
Daniel Webster said this:
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Danijel Vebster je rekao ovo:
14:51
He said, "If all of my possessions were taken
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"Kada bi mi oduzeli sve stvari,
14:53
from me with one exception,
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uz jedan izuzetak,
14:56
I would choose to keep the power of communication,
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odabrao bih da zadržim
moć komunikacije,
moć komunikacije,
14:59
for with it, I would regain all the rest."
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jer bih uz njenu pomoć
vratio sve ostalo".
vratio sve ostalo".
15:03
And that's why, of all of these incredible
applications of FreeSpeech,
applications of FreeSpeech,
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Zbog toga, od svih neverovatnih
primena FreeSpeech-a,
primena FreeSpeech-a,
15:08
the one that's closest to my heart
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meni je najdraža
15:11
still remains the ability for this
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mogućnost da se da moć
15:13
to empower children with disabilities
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deci sa invaliditetom,
15:15
to be able to communicate,
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da mogu da mogu da komuniciraju,
15:17
the power of communication,
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moć komunikacije,
15:19
to get back all the rest.
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kako bi mogli da vrate sve ostalo.
15:21
Thank you.
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Hvala vam.
15:22
(Applause)
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(Aplauz)
15:24
Thank you. (Applause)
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Hvala vam.
(Aplauz)
(Aplauz)
15:28
Thank you. Thank you. Thank you. (Applause)
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Hvala vam. Hvala vam.
(Aplauz)
(Aplauz)
15:33
Thank you. Thank you. Thank you. (Applause)
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Hvala vam. Hvala.
(Aplauz)
(Aplauz)
ABOUT THE SPEAKER
Ajit Narayanan - Visual grammar engine inventorAjit Narayanan is the inventor of Avaz, an affordable, tablet-based communication device for people who are speech-impaired.
Why you should listen
Ajit Narayanan is the founder and CEO of Invention Labs, and the inventor of Avaz AAC, the first assistive device aimed at an Indian market that helps people with speech disabilities -- such as cerebral palsy, autism, intellectual disability, aphasia and learning disabilities -- to communicate. Avaz is also available as an iPad app, aimed at children with autism. In 2010, Avaz won the National Award for Empowerment of People with Disabilities from the president of India, and in 2011, Narayanan was listed in MIT Technology Review 35 under 35.
Narayanan is a prolific inventor with more than 20 patent applications. He is an electrical engineer with degrees from IIT Madras. His research interests are embedded systems, signal processing and understanding how the brain perceives language and communication.
Ajit Narayanan | Speaker | TED.com