TED2013
Ajit Narayanan: A word game to communicate in any language
Ajit Narayanan: Igra riječi za komunikaciju na bilo kojem jeziku
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Tijekom rada s djecom koja imaju govorne probleme, Ajit Narayanan osmislio je način razmišljanja o jeziku u slikama, povezivanje riječi i koncepta u „mape“. Ta ideja sada pokreće aplikaciju koja pomaže neverbalnim ljudima komunicirati, a velika ideja iza toga, koncept jezika nazvan 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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¶ Radim s autističnom djecom.
00:15
Specifically, I make technologies
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Točnije, stvaram tehnologije
00:17
to help them communicate.
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koje im pomažu komunicirati.
00:19
Now, many of the problems that children
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Mnogi problemi s kojima se autistična
00:21
with autism face, they have a common source,
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djeca suočavaju imaju zajednički izvor,
00:24
and that source is that they find it difficult
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a taj izvor jest da im je teško
00:26
to understand abstraction, symbolism.
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razumjeti 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 toga imaju mnogo problema s jezikom.
00:36
Let me tell you a little bit about why this is.
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Sada ću vam reći nešto o razlogu zašto.
00:39
You see that this is a picture of a bowl of soup.
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Vidite, ovo je slika zdjele s juhom.
00:43
All of us can see it. All of us understand this.
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Svi možemo to vidjeti.
Svi možemo to razumjeti.
Svi možemo to razumjeti.
00:46
These are two other pictures of soup,
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Ovo su druge dvije slike juhe,
00:48
but you can see that these are more abstract
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ali možete vidjeti da su više apstraktne.
00:50
These are not quite as concrete.
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Ove nisu jednako konkretne.
00:52
And when you get to language,
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A kada stignete do jezika,
00:54
you see that it becomes a word
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vidite da to postaje riječ
00:56
whose look, the way it looks and the way it sounds,
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čija pojava, način na koji
izgleda i način na koji zvuči
izgleda i način na koji zvuči
00:59
has absolutely nothing to do
with what it started with,
with what it started with,
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nema apsolutno ništa s onim čime je počela
01:02
or what it represents, which is the bowl of soup.
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ili s onim što predstavlja,
a to je zdjela juhe.
a to je zdjela juhe.
01:05
So it's essentially a completely abstract,
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To je zapravo potpuno apstraktna,
01:08
a completely arbitrary representation of something
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potpuno proizvoljna predodžba nečega
01:10
which is in the real world,
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što je u stvarnom svijetu,
01:12
and this is something that children with autism
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a to je nešto s čime autistična djeca
01:13
have an incredible amount of difficulty with.
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imaju velikih problema.
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 toga većina ljudi koji rade
s autističnom djecom -
s autističnom djecom -
01:19
speech therapists, educators --
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logopedi, nastavnici -
01:21
what they do is, they try to help children with autism
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ono što rade je da pokušavaju
pomoći autističnoj djeci
pomoći autističnoj djeci
01:24
communicate not with words, but with pictures.
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komunicirati, ne s riječima, već sa slikama.
01:27
So if a child with autism wanted to say,
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Tako da ako bi
autistično dijete htjelo reći,
autistično dijete htjelo reći,
01:29
"I want soup," that child would pick
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„Hoću juhu, “ to dijete bi izabralo
01:31
three different pictures, "I," "want," and "soup,"
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tri različite slike,
„Ja, “ „htjeti, “ i „juha, “
„Ja, “ „htjeti, “ i „juha, “
01:34
and they would put these together,
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i stavili bi ih zajedno,
01:35
and then the therapist or the parent would
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i tada bi terapeut ili roditelj
01:37
understand that this is what the kid wants to say.
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razumio da je to ono što dijete želi reći.
01:39
And this has been incredibly effective;
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I to je bilo nevjerojatno učinkovito;
01:41
for the last 30, 40 years
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zadnjih 30, 40 godina
01:43
people have been doing this.
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ljudi su to radili.
01:45
In fact, a few years back,
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Zapravo, prije nekoliko godina,
01:46
I developed an app for the iPad
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razvio sam aplikaciju za iPad
01:49
which does exactly this. It's called Avaz,
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koja radi upravo to. Zove se Avaz,
01:51
and the way it works is that kids select
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i način na koji radi je da djeca izaberu
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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Te slike se poredaju zajedno
kako bi formirale rečenice,
kako bi formirale rečenice,
01:57
and these sentences are spoken out.
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i te rečenice se izgovaraju.
01:59
So Avaz is essentially converting pictures,
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Tako Avaz zapravo pretvara slike,
02:02
it's a translator, it converts pictures into speech.
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to je prevoditelj, pretvara slike u govor.
02:06
Now, this was very effective.
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I sad, to je bilo jako učinkovito.
02:07
There are thousands of children using this,
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Na tisuće djece koriste ovo,
02:09
you know, all over the world,
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znate, u cijelom svijetu,
02:10
and I started thinking about
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i počeo sam razmišljati o tome
02:12
what it does and what it doesn't do.
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što radi, a što ne radi.
02:15
And I realized something interesting:
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I shvatio sam nešto zanimljivo:
02:17
Avaz helps children with autism learn words.
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Avaz pomaže autističnoj djeci naučiti riječi.
02:21
What it doesn't help them do is to learn
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Ono što im ne pomaže naučiti jesu
02:23
word patterns.
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obrasci riječi.
02:26
Let me explain this in a little more detail.
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Dopustite mi da ovo
objasnim malo detaljnije.
objasnim malo detaljnije.
02:29
Take this sentence: "I want soup tonight."
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Pogledajte ovu rečenicu:
„Večeras hoću juhu.“
„Večeras hoću juhu.“
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 riječi te koje
ovdje prenose značenje.
ovdje prenose značenje.
02:36
It's also the way in which these words are arranged,
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To je također i način na koji
su ove riječi poslagane,
su ove riječi poslagane,
02:39
the way these words are modified and arranged.
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način na koji su ove riječi
promijenjene i poslagane.
promijenjene i poslagane.
02:41
And that's why a sentence like "I want soup tonight"
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I zbog toga rečenica kao što je
„Hoću juhu večeras“
„Hoću juhu večeras“
02:44
is different from a sentence like
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je drukčija od rečenice kao što je
02:46
"Soup want I tonight," which
is completely meaningless.
is completely meaningless.
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„Juha htjeti ja večeras, “
koja je potpuno beznačajna.
koja je potpuno beznačajna.
02:49
So there is another hidden abstraction here
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Tako je ovdje još jedna 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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s kojom se autistična djeca teško nose,
02:55
and that's the fact that you can modify words
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a to je činjenica da možete mijenjati riječi
02:58
and you can arrange them to have
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i poslagati ih tako da imaju
03:00
different meanings, to convey different ideas.
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različita značenja,
da prenose različite ideje.
da prenose različite ideje.
03:03
Now, this is what we call grammar.
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I sad, to je ono što nazivamo gramatika.
03:07
And grammar is incredibly powerful,
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A gramatika je nevjerojatno snažna,
03:09
because grammar is this one component of language
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jer je gramatika ta jedna komponenta jezika
03:12
which takes this finite vocabulary that all of us have
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koja uzima ograničeni
vokabular riječi koji svi imamo
vokabular riječi koji svi imamo
03:15
and allows us to convey an
infinite amount of information,
infinite amount of information,
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i dopušta nam prenositi
beskonačno mnogo informacija,
beskonačno mnogo informacija,
03:20
an infinite amount of ideas.
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beskonačno mnogo ideja.
03:22
It's the way in which you can put things together
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To je način na koji možete složiti stvari
03:24
in order to convey anything you want to.
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kako bi prenijeli sve što želite.
03:26
And so after I developed Avaz,
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I tako nakon što sam razvio Avaz,
03:28
I worried for a very long time
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brinuo sam se dugo vremena
03:30
about how I could give grammar
to children with autism.
to children with autism.
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o tome kako mogu dati
gramatiku autističnoj djeci.
gramatiku autističnoj djeci.
03:34
The solution came to me from
a very interesting perspective.
a very interesting perspective.
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Rješenje mi je došlo iz jedne
jako zanimljive perspektive.
jako zanimljive perspektive.
03:36
I happened to chance upon a child with autism
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Igrom slučaja naišao sam
na autistično dijete
na autistično dijete
03:39
conversing with her mom,
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koje je razgovaralo sa svojom mamom,
03:41
and this is what happened.
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i dogodilo se ovo.
03:44
Completely out of the blue, very spontaneously,
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Potpuno iznenadno, vrlo spontano,
03:46
the child got up and said, "Eat."
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dijete se ustalo i reklo, „Jesti. “
03:48
Now what was interesting was
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I ono što je bilo zanimljivo jest
03:50
the way in which the mom was trying to tease out
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način na koji je mama pokušala izvući
03:54
the meaning of what the child wanted to say
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značenje onoga što je dijete htjelo reći
03:56
by talking to her in questions.
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tako što joj je pričala u pitanjima.
03:59
So she asked, "Eat what? Do
you want to eat ice cream?
you want to eat ice cream?
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Tako ju je pitala, „Jesti što?
Želiš li jesti sladoled?
Želiš li jesti sladoled?
04:01
You want to eat? Somebody else wants to eat?
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Ti želiš jesti? Netko drugi želi jesti?
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 sad jesti sladoled?
Želiš jesti sladoled navečer?“
Želiš jesti sladoled navečer?“
04:07
And then it struck me that
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Sinulo mi je da
04:08
what the mother had done was something incredible.
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to što je majka napravila
je bilo nešto nevjerojatno.
je bilo nešto nevjerojatno.
04:10
She had been able to get that child to communicate
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Uspjela je navesti to dijete da joj prenese
04:12
an idea to her without grammar.
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neku ideju bez gramatike.
04:16
And it struck me that maybe this is what
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I sinulo mi je da možda je to ono
04:19
I was looking for.
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što sam tražio.
04:20
Instead of arranging words in an order, in sequence,
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Umjesto slaganja riječ u poredak, u slijed,
04:25
as a sentence, you arrange them
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kao rečenicu, slažete ih
04:27
in this map, where they're all linked together
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u ovu mapu, gdje su zajedno povezane
04:31
not by placing them one after the other
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ne sa redanjem jedne iza druge
04:33
but in questions, in question-answer pairs.
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nego sa pitanjima, u parovima pitanje-odgovor.
04:36
And so if you do this, then what you're conveying
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I ako to tako napravite, ono što prenosite
04:38
is not a sentence in English,
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nije rečenica na engleskom,
04:40
but what you're conveying is really a meaning,
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već ono što prenosite je zapravo 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 na neki način
zapravo podzemlje jezika.
zapravo podzemlje jezika.
04:48
It's what comes after thought but before language.
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Ono dolazi poslije misli ali prije jezika.
04:52
And the idea was that this particular representation
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I ideja je bila da ovaj osobit prikaz
04:54
might convey meaning in its raw form.
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bi mogao prenijeti značenje u svome sirovom obliku.
04:57
So I was very excited by this, you know,
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Zato sam bio jako uzbuđen zbog toga, znate,
04:59
hopping around all over the place,
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skakutajući okolo i naokolo
05:01
trying to figure out if I can convert
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pokušavajući odgonetnuti mogu li pretvoriti
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 shvatio sam da to nije dovoljno.
05:07
Why is this not enough?
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Zašto to nije dovoljno?
05:08
This is not enough because if you wanted to convey
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Nije dovoljno zato
što ako biste htjeli prenijeti
što ako biste htjeli prenijeti
05:10
something like negation,
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nešto kao što je negacija,
05:12
you want to say, "I don't want soup,"
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želite reći, „Neću juhu, “
05:14
then you can't do that by asking a question.
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tada to ne možete napraviti
postavljanjem pitanja.
postavljanjem pitanja.
05:16
You do that by changing the word "want."
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To ćete napraviti
mijenjanjem riječi „htjeti“.
mijenjanjem riječi „htjeti“.
05:18
Again, if you wanted to say,
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Ili ako biste htjeli reći,
05:20
"I wanted soup yesterday,"
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„Htio sam juhu jučer, “
05:22
you do that by converting
the word "want" into "wanted."
the word "want" into "wanted."
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to ćete napraviti pretvaranjem riječi „htjeti“ u „htio“.
05:25
It's a past tense.
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To je prošlo vrijeme.
05:26
So this is a flourish which I added
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To je ukras koji sam dodao
05:28
to make the system complete.
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kako bih upotpunio sustav.
05:30
This is a map of words joined together
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Ovo je mapa riječi pridruženih zajedno
05:32
as questions and answers,
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kao pitanja i odgovori,
05:34
and with these filters applied on top of them
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i sa ovim filtrima nadodanim na njih
05:36
in order to modify them to represent
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kako bi ih promijenili da predstavljaju
05:38
certain nuances.
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određene nijanse.
05:39
Let me show you this with a different example.
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Sada ću vam to pokazati
na drukčijem primjeru.
na drukčijem primjeru.
05:41
Let's take this sentence:
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Uzmimo ovu rečenicu:
05:43
"I told the carpenter I could not pay him."
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„Rekao sam stolaru da mu
nisam mogao platiti.“
nisam mogao platiti.“
05:45
It's a fairly complicated sentence.
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To je poprilično složena rečenica.
05:46
The way that this particular system works,
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Način na koji ovaj radi jest da
05:48
you can start with any part of this sentence.
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možete početi s bilo kojim dijelom ove rečenice.
05:51
I'm going to start with the word "tell."
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Počet ću sa riječju „govoriti“.
05:53
So this is the word "tell."
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Dakle ovo je riječ „govoriti“.
05:54
Now this happened in the past,
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Budući da se ovo dogodilo u prošlosti,
05:56
so I'm going to make that "told."
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pa ću promijeniti to u „govorio“.
05:58
Now, what I'm going to do is,
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Sad, ono što ću napraviti jest da
06:00
I'm going to ask questions.
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ću postavljati pitanja.
06:01
So, who told? I told.
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Dakle, tko je rekao? Ja sam rekao.
06:04
I told whom? I told the carpenter.
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Rekao sam kome? Rekao sam stolaru.
06:06
Now we start with a different part of the sentence.
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Sada počinjemo s
drukčijim dijelom rečenice.
drukčijim dijelom rečenice.
06:07
We start with the word "pay,"
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Počinjemo s riječju „platiti“
06:09
and we add the ability filter to it to make it "can pay."
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i dodamo filtar mogućnosti kako
bismo ju promijenili u „mogu platiti“.
bismo ju promijenili u „mogu platiti“.
06:14
Then we make it "can't pay,"
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Potom ju promijenimo u „ne mogu platiti“,
06:16
and we can make it "couldn't pay"
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i možemo ju promijeniti u „nisam mogao platiti“
06:18
by making it the past tense.
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stavljajući ju u prošlo vrijeme.
06:19
So who couldn't pay? I couldn't pay.
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Tko nije mogao platiti?
Ja nisam mogao platiti.
Ja nisam mogao platiti.
06:21
Couldn't pay whom? I couldn't pay the carpenter.
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Kome nisam mogao platiti?
Nisam mogao platiti stolaru.
Nisam mogao platiti stolaru.
06:24
And then you join these two together
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I potom spojite to dvoje zajedno
06:25
by asking this question:
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postavljanjem ovog pitanja:
06:27
What did I tell the carpenter?
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Što sam rekao stolaru?
06:29
I told the carpenter I could not pay him.
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Rekao sam stolaru da
mu nisam mogao platiti.
mu nisam mogao platiti.
06:33
Now think about this. This is
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1937
Sada razmislite o tome. To je
06:35
—(Applause)—
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—(Pljesak)—
06:38
this is a representation of this sentence
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to je prikaz ove rečenice
06:42
without language.
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bez jezika.
06:44
And there are two or three
interesting things about this.
interesting things about this.
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I postoje dvije ili tri
zanimljive stvari oko toga.
zanimljive stvari oko toga.
06:46
First of all, I could have started anywhere.
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Prvo, mogao sam početi bilo gdje.
06:50
I didn't have to start with the word "tell."
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Nisam morao početi s riječju „govoriti“ .
06:52
I could have started anywhere in the sentence,
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Mogao sam početi bilo gdje u rečenici
06:53
and I could have made this entire thing.
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I napraviti cijelu tu stvar.
06:55
The second thing is, if I wasn't an English speaker,
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Druga stvar je da, da nisam
govornik engleskog jezika,
govornik engleskog jezika,
06:57
if I was speaking in some other language,
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da govorim neki drugi jezik,
07:00
this map would actually hold true in any language.
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ova bi mapa zapravo bila
točna u bilo kojem jeziku.
točna u bilo kojem jeziku.
07:03
So long as the questions are standardized,
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1990
Dokle god su pitanja standardizirana,
07:05
the map is actually independent of language.
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mapa je zapravo neovisna o jeziku.
07:09
So I call this FreeSpeech,
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Zato ovo nazivam FreeSpeech (SlobodniGovor)
07:11
and I was playing with this for many, many months.
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i igrao sam se s time mnogo, mnogo mjeseci.
07:14
I was trying out so many
different combinations of this.
different combinations of this.
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Isprobavao sam toliko mnogo
različitih kombinacija toga.
različitih kombinacija toga.
07:17
And then I noticed something very
interesting about FreeSpeech.
interesting about FreeSpeech.
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I tada sam primijetio nešto
vrlo zanimljivo o FreeSpeechu.
vrlo zanimljivo o FreeSpeechu.
07:19
I was trying to convert language,
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Pokušavao sam pretvoriti jezik,
07:22
convert sentences in English
into sentences in FreeSpeech,
into sentences in FreeSpeech,
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pretvoriti rečenice na engleskom
u FreeSpeech rečenice,
u FreeSpeech rečenice,
07:25
and vice versa, and back and forth.
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i obrnuto.
07:27
And I realized that this particular configuration,
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I shvatio sam da mi je
ova osobita konfiguracija,
ova osobita konfiguracija,
07:29
this particular way of representing language,
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2026
ovaj osobit način prikazivanja jezika,
07:31
it allowed me to actually create very concise rules
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dopustio da zapravo stvorim
vrlo jezgrovita pravila
vrlo jezgrovita pravila
07:35
that go between FreeSpeech on one side
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koja idu između FreeSpeecha s jedne strane
07:38
and English on the other.
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i engleskog jezika s druge.
07:39
So I could actually write this set of rules
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Tako da sam zapravo
mogao napisati skup pravila
mogao napisati skup pravila
07:42
that translates from this particular
representation into English.
representation into English.
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koji prevodi ovaj osobit
prikaz na engleski.
prikaz na engleski.
07:45
And so I developed this thing.
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I tako sam razvio ovu stvar.
07:47
I developed this thing called
the FreeSpeech Engine
the FreeSpeech Engine
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Razvio sam stvar zvanu FreeSpeech Motor
07:49
which takes any FreeSpeech sentence as the input
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koja uzima bilo koju
FreeSpeech rečenicu kao unos
FreeSpeech rečenicu kao unos
07:52
and gives out perfectly grammatical English text.
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i izbacuje savršeno gramatički engleski tekst.
07:56
And by putting these two pieces together,
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I spajajući ta dva dijela zajedno,
07:57
the representation and the engine,
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1881
taj prikaz i taj motor,
07:59
I was able to create an app, a
technology for children with autism,
technology for children with autism,
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Mogao sam stvoriti aplikaciju,
tehnologiju za autističnu djecu,
tehnologiju za autističnu djecu,
08:03
that not only gives them words
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2499
koja im ne daje samo riječi
08:05
but also gives them grammar.
195
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3941
već i gramatiku.
08:09
So I tried this out with kids with autism,
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2360
Tako sam isprobao ovo s autističnom djecom,
08:12
and I found that there was an
incredible amount of identification.
incredible amount of identification.
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5013
i vidio sam da je tu postojala
velika količina poistovjećenosti
velika količina poistovjećenosti
08:17
They were able to create sentences in FreeSpeech
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2720
Mogli su stvoriti rečenice u FreeSpeechu
08:19
which were much more complicated
but much more effective
but much more effective
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koje su bile mnogo složenije
i mnogo djelotvornije
i mnogo djelotvornije
08:22
than equivalent sentences in English,
200
490434
2899
nego odgovarajuće rečenice na engleskom,
08:25
and I started thinking about
201
493333
1682
i počeo sam razmišljati 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.
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4287
I dobio sam ideju, i sada želim
s vama razgovarati o njoj.
s vama razgovarati o njoj.
08:33
In about 1997, about 15 years back,
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501271
3142
Negdje oko 1997. , oko prije 15 godina,
08:36
there were a group of scientists that were trying
205
504413
2011
bila je jedna grupa znanstvenika
koji su pokušavali
koji su pokušavali
08:38
to understand how the brain processes language,
206
506424
2389
razumjeti kako mozak obrađuje jezik,
08:40
and they found something very interesting.
207
508813
1779
i otkrili su nešto vrlo zanimljivo.
08:42
They found that when you learn a language
208
510592
1872
Otkrili su da kad učite jezik
08:44
as a child, as a two-year-old,
209
512464
2912
kao dijete, kao jedan dvogodišnjak,
08:47
you learn it with a certain part of your brain,
210
515376
2366
učite ga sa određenim dijelom svoga mozga,
08:49
and when you learn a language as an adult --
211
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1600
a kad učite jezik kao odrastao čovjek –
08:51
for example, if I wanted to
learn Japanese right now —
learn Japanese right now —
212
519342
3911
naprimjer, ako bih sada
htio naučiti japanski –
htio naučiti japanski –
08:55
a completely different part of my brain is used.
213
523253
2707
koristit će se potpuno
drugi dio moga mozga.
drugi dio moga mozga.
08:57
Now I don't know why that's the case,
214
525960
1831
I sad, ne znam zašto je to slučaj,
08:59
but my guess is that that's because
215
527791
1991
ali moja pretpostavka je
da je to zbog toga što
da je to zbog toga što
09:01
when you learn a language as an adult,
216
529782
2437
kada učite jezik kao odrastao čovjek,
09:04
you almost invariably learn it
217
532219
1616
gotovo neizbježno ga učite
09:05
through your native language, or
through your first language.
through your first language.
218
533835
4266
kroz svoj materinji jezik,
kroz svoj prvi jezik.
kroz svoj prvi jezik.
09:10
So what's interesting about FreeSpeech
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3252
Pa ono što je zanimljivo za FreeSpeech
09:13
is that when you create a sentence
220
541353
1802
jest da kada stvarate neku 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,
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3070
autistično dijete stvara
jezik sa FreeSpeechom,
jezik sa FreeSpeechom,
09:19
they're not using this support language,
223
547920
1833
ono ne koristi ovaj potporni jezik,
09:21
they're not using this bridge language.
224
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2211
ne koriste ovaj premosni jezik.
09:23
They're directly constructing the sentence.
225
551964
2657
Direktno sastavljaju rečenicu.
09:26
And so this gave me this idea.
226
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2193
I to mi je dalo ovu ideju
09:28
Is it possible to use FreeSpeech
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2024
Je li moguće koristiti FreeSpeech
09:30
not for children with autism
228
558838
2510
ne za autističnu djecu
09:33
but to teach language to people without disabilities?
229
561348
6262
već za učenje jezika ljudi
bez poteškoća u razvoju?
bez poteškoća u razvoju?
09:39
And so I tried a number of experiments.
230
567610
1978
I tako sam isprobao nekoliko pokusa.
09:41
The first thing I did was I built a jigsaw puzzle
231
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2948
Prvu stvar koju sam napravio je
bila da sam napravio slagalicu
bila da sam napravio slagalicu
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
kodirana u obliku oblika,
09:48
in the form of colors,
234
576341
1138
u obliku boja,
09:49
and you have people putting these together
235
577479
1849
i imate ljude koji ih spajaju
09:51
and trying to understand how this works.
236
579328
1773
i pokušavaju razumjeti kako to radi.
09:53
And I built an app out of it, a game out of it,
237
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2376
I napravio sam aplikaciju
od toga, igricu od toga,
od toga, igricu od toga,
09:55
in which children can play with words
238
583477
2661
u kojoj se djeca mogu igrati riječima
09:58
and with a reinforcement,
239
586138
1704
i sa potkrjepljenjem,
09:59
a sound reinforcement of visual structures,
240
587842
2585
zvučnim potkrjepljenjem
slikovnih struktura
slikovnih struktura
10:02
they're able to learn language.
241
590427
2013
mogu naučiti jezik.
10:04
And this, this has a lot of potential, a lot of promise,
242
592440
2736
I ovo, ovo ima mnogo
mogućnosti, mnogo obećava.
mogućnosti, mnogo obećava.
10:07
and the government of India recently
243
595176
1975
nedavno je indijska vlada
10:09
licensed this technology from us,
244
597151
1404
licencirala 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 isprobat će je sa
milijunima različite djece
milijunima različite djece
10:12
trying to teach them English.
246
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2605
pokušavajući naučiti ih engleski.
10:15
And the dream, the hope, the vision, really,
247
603234
2614
I san, nada, vizija, zapravo,
10:17
is that when they learn English this way,
248
605848
3082
je da kada uče engleski na ovaj način,
10:20
they learn it with the same proficiency
249
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2643
uče ga sa jednakom spretnošću
10:23
as their mother tongue.
250
611573
3718
kao i svoj materinji jezik.
10:27
All right, let's talk about something else.
251
615291
3816
Dobro, razgovarajmo sada o nečem drugom.
10:31
Let's talk about speech.
252
619107
1997
Razgovarajmo o govoru.
10:33
This is speech.
253
621104
1271
Ovo je govor.
10:34
So speech is the primary mode of communication
254
622375
1962
Govor je osnovni način 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
Ono što je zanimljivo kod govora jest da
10:39
speech is one-dimensional.
257
627805
1245
je govor jednodimenzionalan.
10:41
Why is it one-dimensional?
258
629050
1359
Zašto je jednodimenzionalan?
10:42
It's one-dimensional because it's sound.
259
630409
1568
Jednodimenzionalan je zato što je zvuk.
10:43
It's also one-dimensional because
260
631977
1539
Također je jednodimenzionalan zato što
10:45
our mouths are built that way.
261
633516
1205
su naša usta tako građena.
10:46
Our mouths are built to create
one-dimensional sound.
one-dimensional sound.
262
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3512
Naša usta su građena tako da
stvaraju jednodimenzionalni zvuk.
stvaraju jednodimenzionalni zvuk.
10:50
But if you think about the brain,
263
638233
2866
Ali ako razmišljate o mozgu,
10:53
the thoughts that we have in our heads
264
641099
1764
misli koje imamo u našim glavama
10:54
are not one-dimensional.
265
642863
2102
nisu jednodimenzionalne.
10:56
I mean, we have these rich,
266
644965
1459
Hoću reći, imamo te bogate,
10:58
complicated, multi-dimensional ideas.
267
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3028
složene, višedimenzionalne ideje.
11:01
Now, it seems to me that language
268
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1690
Sad, meni se čini da jezik
11:03
is really the brain's invention
269
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2332
je zapravo izum mozga
11:05
to convert this rich, multi-dimensional thought
270
653474
3096
kojim pretvara te bogatu,
višedimenzionalnu misao
višedimenzionalnu misao
11:08
on one hand
271
656570
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
660080
1762
Ono što je zanimljivo jest da
11:13
we do a lot of work in information nowadays,
274
661842
2568
mi u današnje vrijeme radimo
mnogo posla u informacijama,
mnogo posla u informacijama,
11:16
and almost all of that is done
in the language domain.
in the language domain.
275
664410
3079
a gotovo sve to se radi u domeni jezika.
11:19
Take Google, for example.
276
667489
1939
Uzmite naprimjer Google.
11:21
Google trawls all these
countless billions of websites,
countless billions of websites,
277
669428
2677
Google iskopava bezbroj milijardi
svih tih web stranica,
svih tih web stranica,
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
koje su sve na engleskom,
i kad želite koristiti Google,
i kad želite koristiti Google,
11:26
you go into Google search, and you type in English,
279
674830
2450
idete na Google pretraživanje,
i tipkate na engleskom,
i tipkate na engleskom,
11:29
and it matches the English with the English.
280
677280
4163
i on sparuje engleski sa engleskim.
11:33
What if we could do this in FreeSpeech instead?
281
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3583
Što ako bismo to mogli napraviti u FreeSpeechu?
11:37
I have a suspicion that if we did this,
282
685026
2301
Imam sumnju da ako bismo to napravili,
11:39
we'd find that algorithms like searching,
283
687327
2068
otkrili bismo da
algoritmi kao pretraživanje,
algoritmi kao pretraživanje,
11:41
like retrieval, all of these things,
284
689395
2325
kao dohvaćanje, sve te stvari,
11:43
are much simpler and also more effective,
285
691720
3075
su mnogo jednostavniji i
također mnogo učinkovitiji,
također mnogo učinkovitiji,
11:46
because they don't process
the data structure of speech.
the data structure of speech.
286
694795
4417
jer oni ne obrađuju
podatkovnu strukturu govora.
podatkovnu strukturu govora.
11:51
Instead they're processing
the data structure of thought.
the data structure of thought.
287
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5976
Umjesto toga obrađuju
podatkovnu strukturu misli.
podatkovnu strukturu misli.
11:57
The data structure of thought.
288
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2808
Podatkovna struktura misli.
11:59
That's a provocative idea.
289
707996
2076
To je provokativna ideja.
12:02
But let's look at this in a little more detail.
290
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2142
Ali pogledajmo to malo detaljnije.
12:04
So this is the FreeSpeech ecosystem.
291
712214
2366
Dakle, ovo je FreeSpeech ekosustav.
12:06
We have the Free Speech
representation on one side,
representation on one side,
292
714580
2884
Imamo Free Speech
prikaz s jedne strane
prikaz s jedne strane
12:09
and we have the FreeSpeech
Engine, which generates English.
Engine, which generates English.
293
717464
2228
i imamo FreeSpeech motor,
koji stvara engleski.
koji stvara engleski.
12:11
Now if you think about it,
294
719694
1725
Sada ako razmislite o tome,
12:13
FreeSpeech, I told you, is completely
language-independent.
language-independent.
295
721419
2544
FreeSpeech, kao što sam vam rekao,
je potpuno neovisan o jeziku.
je potpuno neovisan o jeziku.
12:15
It doesn't have any specific information in it
296
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2087
Nema nikakve specifične informacije u sebi
12:18
which is about English.
297
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1228
koja je o engleskom jeziku.
12:19
So everything that this system knows about English
298
727278
2800
Sve što taj sustav zna o engleskom
12:22
is actually encoded into the engine.
299
730078
4620
je kodirano u programu.
12:26
That's a pretty interesting concept in itself.
300
734698
2237
To je vrlo zanimljiv koncept sam po sebi.
12:28
You've encoded an entire human language
301
736935
3604
Kodirali ste cijeli ljudski jezik
12:32
into a software program.
302
740539
2645
u jedan program.
12:35
But if you look at what's inside the engine,
303
743184
2531
Ali ako pogledate što je unutar programa,
12:37
it's actually not very complicated.
304
745715
2358
zapravo to nije tako složeno.
12:40
It's not very complicated code.
305
748073
2105
To nije jako složen kod.
12:42
And what's more interesting is the fact that
306
750178
2672
I ono što je još zanimljivije je činjenica
12:44
the vast majority of the code in that engine
307
752850
2203
da velika većina koda u programu
12:47
is not really English-specific.
308
755053
2412
nije zapravo specifična za engleski.
12:49
And that gives this interesting idea.
309
757465
1895
I iz toga proizlazi ova zanimljiva ideja.
12:51
It might be very easy for us to actually
310
759360
2038
Moglo bi nam biti vrlo lako zapravo
12:53
create these engines in many,
many different languages,
many different languages,
311
761398
3826
stvoriti takve programe u mnogo,
mnogo različitih jezika,
mnogo različitih jezika,
12:57
in Hindi, in French, in German, in Swahili.
312
765224
6354
na hindskom, francuskom,
njemačkom, swahiliju.
njemačkom, swahiliju.
13:03
And that gives another interesting idea.
313
771578
2799
A iz toga proizlazi još jedna
zanimljiva ideja.
zanimljiva ideja.
13:06
For example, supposing I was a writer,
314
774377
2654
Naprimjer, recimo da sam pisac,
13:09
say, for a newspaper or for a magazine.
315
777031
2122
ne znam, za neke novine ili časopis.
13:11
I could create content in one language, FreeSpeech,
316
779153
5011
Mogao bih stvoriti sadržaj na
jednom jeziku, FreeSpeechu,
jednom jeziku, FreeSpeechu,
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
786220
3061
osoba koja čita te informacije
13:21
could choose any engine,
319
789281
2495
mogla bi odabrati bilo koji program,
13:23
and they could read it in their own mother tongue,
320
791776
2736
i pročitati to na svojem materinjem jeziku,
13:26
in their native language.
321
794512
3939
na svojem vlastitom jeziku.
13:30
I mean, this is an incredibly attractive idea,
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Hoću reći, to je vrlo privlačna ideja,
13:33
especially for India.
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posebno za Indiju.
13:35
We have so many different languages.
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Imamo toliko mnogo različitih jezika.
13:36
There's a song about India, and there's a description
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Ima jedna pjesma o Indiji, i postoji opis
13:39
of the country as, it says,
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zemlje koji kaže,
13:41
(in Sanskrit).
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(na sanskrtskom)
13:43
That means "ever-smiling speaker
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To znači „vječno nasmijan govornik
13:46
of beautiful languages."
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prekrasnih jezika.“
13:51
Language is beautiful.
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Jezik je prekrasan.
13:52
I think it's the most beautiful of human creations.
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Mislim da je to najljepša od
svih ljudskih tvorevina.
svih ljudskih tvorevina.
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 najdivnija stvar
koju su naši mozgovi izmislili.
koju su naši mozgovi izmislili.
13:59
It entertains, it educates, it enlightens,
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Zabavlja, obrazuje, prosvjetljuje,
14:02
but what I like the most about language
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ali ono što mi se najviše sviđa kod jezika
14:05
is that it empowers.
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jest da osnažuje.
14:06
I want to leave you with this.
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Htio bih završiti s ovim.
14:08
This is a photograph of my collaborators,
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Ovo je fotografija mojih suradnika,
14:10
my earliest collaborators
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mojih najranijih suradnika
14:11
when I started working on language
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kada sam počeo raditi 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 djevojčice je Pavna,
14:16
and that's her mother, Kalpana.
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I to je njezina majka, Kalpana.
14:18
And Pavna's an entrepreneur,
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I Pavna je poduzetnica,
14:20
but her story is much more remarkable than mine,
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ali njezina priča je mnogo
vrjednija pažnje no moja,
vrjednija pažnje no moja,
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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Ima kvadriplegičnu cerebralnu paralizu,
14:27
so ever since she was born,
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od vremena kad se rodila,
14:29
she could neither move nor talk.
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nije se mogla micati ni govorit.
14:32
And everything that she's accomplished so far,
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I sve što je dosad 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 tvrtke,
14:38
collaborating with me to develop Avaz,
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suradnja sa mnom u razvijanju Avaza,
14:40
all of these things she's done
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sve te stvari je postigla
14:42
with nothing more than moving her eyes.
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s ništa više od micanja očiju.
14:48
Daniel Webster said this:
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Daniel Webster je rekao ovo:
14:51
He said, "If all of my possessions were taken
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Rekao je, „Kad bi mi
sve što imam bilo oduzeto
sve što imam bilo oduzeto
14:53
from me with one exception,
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s jednom iznimkom,
14:56
I would choose to keep the power of communication,
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odabrao bih zadržati moć komunikacije,
14:59
for with it, I would regain all the rest."
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jer bi s njom ponovno stekao sve ostalo.“
15:03
And that's why, of all of these incredible
applications of FreeSpeech,
applications of FreeSpeech,
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I zbog toga, od svih ovih
nevjerojatnih primjena FreeSpeecha,
nevjerojatnih primjena FreeSpeecha,
15:08
the one that's closest to my heart
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ona koja mi je najbliža srcu
15:11
still remains the ability for this
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još uvijek ostaje njegova mogućnost
15:13
to empower children with disabilities
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da omogući djeci s poteškoćama
15:15
to be able to communicate,
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sposobnost komunikacije,
15:17
the power of communication,
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snagu komunikacije,
15:19
to get back all the rest.
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kako bi dobila nazad sve ostalo.
15:21
Thank you.
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Hvala.
15:22
(Applause)
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(Pljesak)
15:24
Thank you. (Applause)
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Hvala. (Pljesak)
15:28
Thank you. Thank you. Thank you. (Applause)
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Hvala. Hvala. Hvala. (Pljesak)
15:33
Thank you. Thank you. Thank you. (Applause)
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Hvala. Hvala. Hvala. (Pljesak)
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