I work with children with autism. Specifically, I make technologies to help them communicate.
Ja radim sa decom sa autizmom. Tačnije, razvijam tehnologije koje im pomažu da komuniciraju.
Now, many of the problems that children with autism face, they have a common source, and that source is that they find it difficult to understand abstraction, symbolism. And because of this, they have a lot of difficulty with language.
Mnogi problemi sa kojima se deca sa autizmom suočavaju, imaju isti izvor, a to je da im je veoma teško da razumeju apstrakciju, simbolizam. Zbog ovoga, ona imaju mnogo poteškoća sa jezikom.
Let me tell you a little bit about why this is. You see that this is a picture of a bowl of soup. All of us can see it. All of us understand this. These are two other pictures of soup, but you can see that these are more abstract These are not quite as concrete. And when you get to language, you see that it becomes a word whose look, the way it looks and the way it sounds, has absolutely nothing to do with what it started with, or what it represents, which is the bowl of soup. So it's essentially a completely abstract, a completely arbitrary representation of something which is in the real world, and this is something that children with autism have an incredible amount of difficulty with. Now that's why most of the people that work with children with autism -- speech therapists, educators -- what they do is, they try to help children with autism communicate not with words, but with pictures. So if a child with autism wanted to say, "I want soup," that child would pick three different pictures, "I," "want," and "soup," and they would put these together, and then the therapist or the parent would understand that this is what the kid wants to say. And this has been incredibly effective; for the last 30, 40 years people have been doing this. In fact, a few years back, I developed an app for the iPad which does exactly this. It's called Avaz, and the way it works is that kids select different pictures. These pictures are sequenced together to form sentences, and these sentences are spoken out. So Avaz is essentially converting pictures, it's a translator, it converts pictures into speech.
Dozvolite mi da vam kažem malo o tome zašto je to tako. Ovo je slika činije sa supom. Svi mi to vidimo. Svi mi razumemo to. Ovo su dve druge slike supe, ali su one apstraktnije. Nisu u tolikoj meri konkretne. A kada stignemo do jezika, vidimo da ona postaje reč, čiji izgled, kako izgleda i kako zvuči, nema nikakve veze sa onim od čega je potekla ili sa onim što predstavlja, a to je činija supe. Ona je u suštini u potpunosti apstraktna, potpuno arbitrarna reprezentacija nečega što je u stvarnom svetu i to je nešto sa čime deca sa autizmom imaju neverovatnih poteškoća. Zbog ovoga većina ljudi koji rade sa decom sa autizmom - govorni terapeuti, učitelji - pokušavaju da pomognu deci sa autizmom da komuniciraju, ne rečima, nego putem slika. Ako bi dete sa autizmom želelo da kaže: "Želim supu", to dete bi izabralo tri različite slike: "ja", "želeti" i "supa" i spojilo bi ih i tako bi terapeut ili roditelj razumeo da je to ono što dete želi da kaže. Ovo je bilo izuzetno efikasno; ljudi su radili ovo u proteklih 30, 40 godina. U stvari, pre nekoliko godina, razvio sam aplikaciju za Ajped koja radi upravo ovo. Ona se zove Avaz, a radi tako što dete bira različite slike. Ove slike su poređane u nizu i stvaraju rečenice, a onda se ove rečenice izgovaraju. Avaz u suštini radi konverziju, on je prevodilac koji pretvara slike u govor.
Now, this was very effective. There are thousands of children using this, you know, all over the world, and I started thinking about what it does and what it doesn't do. And I realized something interesting: Avaz helps children with autism learn words. What it doesn't help them do is to learn word patterns. Let me explain this in a little more detail. Take this sentence: "I want soup tonight." Now it's not just the words here that convey the meaning. It's also the way in which these words are arranged, the way these words are modified and arranged. And that's why a sentence like "I want soup tonight" is different from a sentence like "Soup want I tonight," which is completely meaningless. So there is another hidden abstraction here which children with autism find a lot of difficulty coping with, and that's the fact that you can modify words and you can arrange them to have different meanings, to convey different ideas. Now, this is what we call grammar. And grammar is incredibly powerful, because grammar is this one component of language which takes this finite vocabulary that all of us have and allows us to convey an infinite amount of information, an infinite amount of ideas. It's the way in which you can put things together in order to convey anything you want to.
Ovo je bilo veoma efikasno. Hiljade dece koristi ovo, znate, širom sveta, i počeo sam da razmišljam o tome šta ono radi, a šta ne radi. I shvatio sam nešto interesantno: Avaz pomaže deci sa autizmom da nauče reči. Ali ne pomaže im da nauče obrasce tih reči. Dozvolite mi da objasnim ovo malo detaljnije. Uzmimo rečenicu: "Želim supu večeras." Nisu samo reči te koje prenose značenje. Tu je i način na koji su te reči poređane, način na koji su one izmenjene i poređane. Zato je rečenica: "Želim supu večeras." drugačija od rečenice kao što je: "Supa želeti ja večeras", koja je u potpunosti besmislena. Tu postoji još jedna skrivena apstrakcija sa kojom se deca sa autizmom teško nose, a to je činjenica da reči možemo da izmenimo i možemo da ih poređamo tako da dobijemo različita značenja, prenesemo različite ideje. To je ono što zovemo gramatikom. Gramatika je izuzetno moćna, jer je gramatika komponenta jezika koja uzima ograničen vokabular koji svi mi imamo i dozvoljava nam da prenesemo neograničenu količinu informacija, beskrajni broj ideja. To je način na koji spajamo stvari kako bismo preneli šta god želimo.
And so after I developed Avaz, I worried for a very long time about how I could give grammar to children with autism. The solution came to me from a very interesting perspective. I happened to chance upon a child with autism conversing with her mom, and this is what happened. Completely out of the blue, very spontaneously, the child got up and said, "Eat." Now what was interesting was the way in which the mom was trying to tease out the meaning of what the child wanted to say by talking to her in questions. So she asked, "Eat what? Do you want to eat ice cream? You want to eat? Somebody else wants to eat? You want to eat cream now? You want to eat ice cream in the evening?" And then it struck me that what the mother had done was something incredible. She had been able to get that child to communicate an idea to her without grammar. And it struck me that maybe this is what I was looking for. Instead of arranging words in an order, in sequence, as a sentence, you arrange them in this map, where they're all linked together not by placing them one after the other but in questions, in question-answer pairs. And so if you do this, then what you're conveying is not a sentence in English, but what you're conveying is really a meaning, the meaning of a sentence in English. Now, meaning is really the underbelly, in some sense, of language. It's what comes after thought but before language. And the idea was that this particular representation might convey meaning in its raw form.
Nakon što sam razvio Avaz, dugo sam razmišljao o tome kako deci sa autizmom da pružim gramatiku. Rešenje mi se javilo iz jednog interesantnog ugla. Sreo sam jedno dete sa autizmom koje je razgovaralo sa svojom majkom i ovo se desilo. Sasvim neočekivano, veoma spontano dete je prišlo i reklo: "Jesti." Ono što je bilo interesantno je bio način na koji je majka pokušavala da odgonetne značenje onoga što je dete želelo da kaže postavljanjem pitanja. Pitala je: "Jesti šta? Želiš li da jedeš sladoled?" Ti želiš da jedeš? Neko drugi želi da jede? Želiš da jedeš sladoled sada? Želiš da jedeš sladoled uveče?" I onda sam shvatio da je majka uradila nešto zaista neverovatno. Ona je navela to dete da joj prenese ideju bez gramatike. I onda sam shvatio da je možda ovo ono što sam tražio. Umesto ređanja reči u nizove, kao rečenice, poređajmo ih na ovu mapu, gde su sve one povezane ne putem njihovog nizanja jednih nakon drugih, već pitanjima, u parovima pitanja i odgovora. Ako uradimo ovo, onda ne prenosimo rečenicu na engleskom, ono što prenosimo je u stvari značenje, značenje rečenice na engleskom. Značenje je u stvari u nekom smislu potpora jezika. To je ono što dolazi nakon misli, ali pre jezika. Ideja je bila da ovaj način predstavljanja može da prenese značenje u njegovom sirovom obliku.
So I was very excited by this, you know, hopping around all over the place, trying to figure out if I can convert all possible sentences that I hear into this. And I found that this is not enough. Why is this not enough? This is not enough because if you wanted to convey something like negation, you want to say, "I don't want soup," then you can't do that by asking a question. You do that by changing the word "want." Again, if you wanted to say, "I wanted soup yesterday," you do that by converting the word "want" into "wanted." It's a past tense. So this is a flourish which I added to make the system complete. This is a map of words joined together as questions and answers, and with these filters applied on top of them in order to modify them to represent certain nuances. Let me show you this with a different example.
Bio sam veoma uzbuđen ovim, znate, skakao sam gore-dole pokušavajući da otkrijem mogu li da pretvorim sve moguće rečenice koje čujem u ovo. I otkrio sam da ovo nije dovoljno. Zašto nije dovoljno? Nije dovoljno, jer ako želite da prenesete nešto kao negaciju, želite da kažete: "Ne želim supu", onda to ne možete da uradite postavljanjem pitanja. To radite promenom reči "želeti". Ukoliko bismo želeli da kažemo: "Želeo sam supu juče", pretvaramo reč "želeti" u "želeo". To je prošlo vreme. Ovo je ono što sam dodao kako bih kompletirao sistem. Ovo je mapa povezanih reči putem pitanja i odgovora, a ovo su filteri primenjeni na njima kako bi pretvorili reči da bi one predstavljale određene nijanse. Pogledajmo to na drugačijem primeru.
Let's take this sentence: "I told the carpenter I could not pay him." It's a fairly complicated sentence. The way that this particular system works, you can start with any part of this sentence. I'm going to start with the word "tell." So this is the word "tell." Now this happened in the past, so I'm going to make that "told." Now, what I'm going to do is, I'm going to ask questions. So, who told? I told. I told whom? I told the carpenter. Now we start with a different part of the sentence. We start with the word "pay," and we add the ability filter to it to make it "can pay." Then we make it "can't pay," and we can make it "couldn't pay" by making it the past tense. So who couldn't pay? I couldn't pay. Couldn't pay whom? I couldn't pay the carpenter. And then you join these two together by asking this question: What did I tell the carpenter? I told the carpenter I could not pay him.
Uzmimo rečenicu: "Rekao sam stolaru da ne mogu da mu platim." Ovo je poprilično složena rečenica. Način na koji ovaj sistem radi je takav da možete da krenete od bilo kog dela ove rečenice. Ja ću krenuti sa rečju: "reći". Ovo je reč "reći". Pošto se ovo desilo u prošlosti, pretvoriću je u "rekao". Sada ću postaviti pitanje. Ko je rekao? Ja sam rekao. Kome sam rekao? Rekao sam stolaru. Sada ćemo krenuti od drugog dela rečenice. Krenućemo od reči "platiti" i dodaćemo filter za mogućnost da bismo je pretvorili u "mogu da platim". Zatim ćemo je pretvoriti u "ne mogu da platim" i onda u "nisam mogao da platim" dodavajući prošlo vreme. Ko nije mogao da plati? Ja nisam mogao da platim. Kome nisam mogao da platim? Nisam mogao da platim stolaru. Onda spojimo ova dva dela postavljanjem pitanja: "Šta sam rekao stolaru? Rekao sam stolaru da ne mogu da mu platim.
Now think about this. This is —(Applause)— this is a representation of this sentence without language. And there are two or three interesting things about this. First of all, I could have started anywhere. I didn't have to start with the word "tell." I could have started anywhere in the sentence, and I could have made this entire thing. The second thing is, if I wasn't an English speaker, if I was speaking in some other language, this map would actually hold true in any language. So long as the questions are standardized, the map is actually independent of language. So I call this FreeSpeech, and I was playing with this for many, many months. I was trying out so many different combinations of this.
Razmislite o ovome. Ovo je - (Aplauz) - ovo je predstavljanje ove rečenice bez jezika. Postoje dve ili tri interesantne stvari u vezi s ovim. Prvo, mogao sam da počnem bilo gde. Nisam morao da krenem sa rečju "reći". Mogao sam da krenem bilo gde i mogao sam da stvorim sve ovo. Druga stvar je, da nisam govornik engleskog, da govorim nekim drugim jezikom, ova mapa bi bila identična u bilo kom jeziku. Dokle god su pitanja standardizovana, ova mapa je u stvari nezavisna od jezika. Ovo sam nazvao FreeSpeech i igrao sam se ovime mnogo meseci. Pokušavao sam mnogo različitih kombinacija
And then I noticed something very interesting about FreeSpeech. I was trying to convert language, convert sentences in English into sentences in FreeSpeech, and vice versa, and back and forth. And I realized that this particular configuration, this particular way of representing language, it allowed me to actually create very concise rules that go between FreeSpeech on one side and English on the other. So I could actually write this set of rules that translates from this particular representation into English. And so I developed this thing. I developed this thing called the FreeSpeech Engine which takes any FreeSpeech sentence as the input and gives out perfectly grammatical English text. And by putting these two pieces together, the representation and the engine, I was able to create an app, a technology for children with autism, that not only gives them words but also gives them grammar.
I onda sam primetio nešto veoma interesantno. Pokušavao sam da pretvorim jezik, rečenice na engleskom u rečenice FreeSpeech-a i obrnuto, u jednom i drugom pravcu. I shvatio sam da mi je ova konfiguracija, ovaj način predstavljanja jezika, da su mi dozvolili da stvorim veoma koncizna pravila koja povezuju FreeSpeech sa jedne strane i engleski s druge. Tako bih mogao na napišem set ovakvih pravila koji prevodi iz ove reprezentacije u engleski. I razvio sam to. Razvio sam takozvani FreeSpeech Engine koji uzima bilo koju FreeSpeech rečenicu kao ulaznu informaciju i daje gramatičnu englesku rečenicu. Spajanjem ova dva dela predstave i mehanizma stvorio sam aplikaciju, tehnologiju za decu sa autizmom koja im ne daje samo reči nego im daje i gramatiku.
So I tried this out with kids with autism, and I found that there was an incredible amount of identification. They were able to create sentences in FreeSpeech which were much more complicated but much more effective than equivalent sentences in English, and I started thinking about why that might be the case. And I had an idea, and I want to talk to you about this idea next. In about 1997, about 15 years back, there were a group of scientists that were trying to understand how the brain processes language, and they found something very interesting. They found that when you learn a language as a child, as a two-year-old, you learn it with a certain part of your brain, and when you learn a language as an adult -- for example, if I wanted to learn Japanese right now — a completely different part of my brain is used. Now I don't know why that's the case, but my guess is that that's because when you learn a language as an adult, you almost invariably learn it through your native language, or through your first language. So what's interesting about FreeSpeech is that when you create a sentence or when you create language, a child with autism creates language with FreeSpeech, they're not using this support language, they're not using this bridge language. They're directly constructing the sentence.
Ispobao sam ovo sa decom sa autizmom i otkrio sam da postoji visok stepen identifikacije. Mogli su da stvaraju rečenice u FreeSpeech-u koje su bile mnogo složenije, ali i efikasnije od ekvivalenata na engleskom i počeo sam da razmišljam o tome zašto je to tako. Imao sam ideju, i želim sada da vam pričam o njoj. 1997, pre oko 15 godina grupa naučnika pokušavala je da razume kako mozak obrađuje jezik i otkrili su nešto veoma interesantno. Otkrili su da kada učimo jezik kao deca, kao dvogodišnjaci, učimo ga sa jednim delom mozga, a kada ga učimo kao odrasli - na primer, ako bih sada želeo da naučim japanski - koristio bih potpuno drugačiji deo mozga. Ne znam zašto je to tako, pretpostavljam da je to zato što kada učimo jezike kao odrasli, skoro stalno ih učimo putem maternjeg jezika ili putem prvog jezika. Ono što je interesantno u vezi FreeSpeech-a je da kada stvarate rečenicu ili kada stvarate jezik, kada dete sa autizmom stvara jezik pomoću FreeSpeech-a, ono ga ne koristi kao pomoćni jezik, kao vezu između dva jezika. Oni direktno stvaraju rečenicu.
And so this gave me this idea. Is it possible to use FreeSpeech not for children with autism but to teach language to people without disabilities? And so I tried a number of experiments. The first thing I did was I built a jigsaw puzzle in which these questions and answers are coded in the form of shapes, in the form of colors, and you have people putting these together and trying to understand how this works. And I built an app out of it, a game out of it, in which children can play with words and with a reinforcement, a sound reinforcement of visual structures, they're able to learn language. And this, this has a lot of potential, a lot of promise, and the government of India recently licensed this technology from us, and they're going to try it out with millions of different children trying to teach them English. And the dream, the hope, the vision, really, is that when they learn English this way, they learn it with the same proficiency as their mother tongue.
Ovo mi je dalo ideju. Da li je moguće koristiti FreeSpeech ne za decu sa autizmom, nego da ljude bez invaliditeta učimo jezicima? Sproveo sam nekoliko eksperimenata. Prva stvar koju sam napravio je slagalica u kojoj su ova pitanja i odgovori pretvoreni u oblike, boje i ljudi ovo slažu i pokušavaju da razumeju kako radi. Napravio sam aplikaciju, igru, u kojoj deca mogu da se igraju rečima, i putem potvrde, zvučne potvrde vizuelnih struktura, oni mogu da nauče jezik. Ovo ima mnogo potencijala, obećava mnogo i vlada Indije je nedavno otkupila ovu tehnologiju od nas i isprobavaju je sa milionima dece pokušavajući da ih nauče engleski. San, nada, vizija je da kada ovako uče engleski oni ga uče sa istom sposobnošću kao svoj maternji jezik.
All right, let's talk about something else. Let's talk about speech. This is speech. So speech is the primary mode of communication delivered between all of us. Now what's interesting about speech is that speech is one-dimensional. Why is it one-dimensional? It's one-dimensional because it's sound. It's also one-dimensional because our mouths are built that way. Our mouths are built to create one-dimensional sound. But if you think about the brain, the thoughts that we have in our heads are not one-dimensional. I mean, we have these rich, complicated, multi-dimensional ideas. Now, it seems to me that language is really the brain's invention to convert this rich, multi-dimensional thought on one hand into speech on the other hand. Now what's interesting is that we do a lot of work in information nowadays, and almost all of that is done in the language domain. Take Google, for example. Google trawls all these countless billions of websites, all of which are in English, and when you want to use Google, you go into Google search, and you type in English, and it matches the English with the English. What if we could do this in FreeSpeech instead? I have a suspicion that if we did this, we'd find that algorithms like searching, like retrieval, all of these things, are much simpler and also more effective, because they don't process the data structure of speech. Instead they're processing the data structure of thought. The data structure of thought. That's a provocative idea.
Hajde da govorimo o nečemu drugom. Hajde da govorimo o govoru. Ovo je govor. Govor je primarno sredstvo komunikacije između svih nas. Kod govora je interesantno to što je on jednodimenzionalan. Zašto je jednodimenzionalan? Zato što je zvuk. Jednodimenzionalan je takođe jer su nam usta tako napravljena. Naša usta su stvorena da stvaraju jednodimenzionalni zvuk. Ali ako razmislite, mozak, misli koje imamo u glavi, nisu jednodimenzionalne. Imamo ove bogate, komplikovane, multi-dimenzionalne ideje. Čini mi se da je jezik u stvari izum mozga kojim pretvara ovu bogatu, multi-dimenzionalnu misao s jedne strane u govor s druge strane. Interesantno je to da danas mnogo radimo sa informacijama i skoro sve što se radi je u domenu jezika. Uzmimo Gugl, na primer. Gugl pročešljava nebrojene milijarde sajtova, od kojih su svi na engleskom, i kada želite da koristite Gugl, idete na Gugl pretragu i kucate na engleskom, i ona upari engleski s engleskim. Šta ako bismo ovo mogli da uradimo sa FreeSpeech-om? Čini mi se da kada bismo ovo uradili, otkrili bismo da su algoritmi poput pretrage, davanja rezultata, sve ove stvari, da je sve to jednostavnije i efikasnije, jer ne mora da se obradi struktura podataka govora. Umesto toga se obrađuje struktura podataka misli. Struktura podataka misli. To je provokativna zamisao.
But let's look at this in a little more detail. So this is the FreeSpeech ecosystem. We have the Free Speech representation on one side, and we have the FreeSpeech Engine, which generates English. Now if you think about it, FreeSpeech, I told you, is completely language-independent. It doesn't have any specific information in it which is about English. So everything that this system knows about English is actually encoded into the engine. That's a pretty interesting concept in itself. You've encoded an entire human language into a software program. But if you look at what's inside the engine, it's actually not very complicated. It's not very complicated code. And what's more interesting is the fact that the vast majority of the code in that engine is not really English-specific. And that gives this interesting idea. It might be very easy for us to actually create these engines in many, many different languages, in Hindi, in French, in German, in Swahili. And that gives another interesting idea. For example, supposing I was a writer, say, for a newspaper or for a magazine. I could create content in one language, FreeSpeech, and the person who's consuming that content, the person who's reading that particular information could choose any engine, and they could read it in their own mother tongue, in their native language. I mean, this is an incredibly attractive idea, especially for India. We have so many different languages. There's a song about India, and there's a description of the country as, it says, (in Sanskrit). That means "ever-smiling speaker of beautiful languages."
Ali hajde da detaljnije pogledamo ovo. Ovo je ekosistem FreeSpeech-a. Sa jedne strane imamo prikaz FreeSpeech-a, i imamo mehanizam FreeSpeech-a, koji stvara engleski. Ako razmislite o tome, rekao sam vam da je FreeSpeech potpuno nezavisan od jezika. U sebi ne sadrži posebne informacije vezane za engleski. Sve što ovaj sistem zna o engleskom je zapravo zapisano u mehanizmu. To je samo po sebi zanimljiv koncept. Kodirali smo čitav ljudski jezik u softverski program. Ali ako pogledate unutar mehanizma, zapravo nije veoma komplikovano. Kod nije veoma komplikovan. A interesantnija je činjenica da je većina koda u tom mehanizmu nevezana za engleski. To nam je dalo zanimljivu ideju. Možda bi bilo lako da zapravo napravimo ove mehanizme u mnogo različitih jezika, indijskom, francuskom, nemačkom, svahiliju. A to nam je dalo još jednu zanimljivu ideju. Na primer, recimo da sam pisac, za novine ili magazin. Mogao bih da stvaram sadržaj u jednom jeziku, FreeSpeech-u, a osoba koja konzumira taj sadržaj, koja čita te informacije, mogla bi da odabere bilo koji mehanizam, i mogla bi da čita to na svom maternjem jeziku. Ovo je neverovatno privlačna ideja, naročito za Indiju. Imamo toliko različitih jezika. Postoji pesma o Indiji, i postoji opis zemlje koji kaže, (na Sanskritu). To znači: "govornik predivnih jezika koji se stalno smeje".
Language is beautiful. I think it's the most beautiful of human creations. I think it's the loveliest thing that our brains have invented. It entertains, it educates, it enlightens, but what I like the most about language is that it empowers.
Jezik je predivan. Mislim da je to najlepša od svih ljudskih kreacija. Mislim da je to najdraža stvar koju su smislili naši mozgovi. On zabavlja, obrazuje, prosvetljuje, ali kod jezika najviše volim to što daje moć.
I want to leave you with this. This is a photograph of my collaborators, my earliest collaborators when I started working on language and autism and various other things. The girl's name is Pavna, and that's her mother, Kalpana. And Pavna's an entrepreneur, but her story is much more remarkable than mine, because Pavna is about 23. She has quadriplegic cerebral palsy, so ever since she was born, she could neither move nor talk. And everything that she's accomplished so far, finishing school, going to college, starting a company, collaborating with me to develop Avaz, all of these things she's done with nothing more than moving her eyes.
Želim da vas ostavim sa ovim. Ovo je fotografija mojih saradnika, najranijih saradnika, kada sam počeo da radim na jeziku i autizmu i drugim stvarima. Ime ove devojčice je Pavna, a to je njena majka, Kalpana. Pavna je preduzetnica, ali njena priča je fascinantnija od moje, jer Pavna ima oko 23 godine. Ona ima cerebralnu paralizu, tako da od svog rođenja nije mogla da se pomera ili priča. Sve što je do sada postigla, završavanje škole, odlazak na fakultet, osnivanje kompanije, saradnja sa mnom na razvijanju Avaza, sve ove stvari je uradila samo uz pomeranje svojih očiju.
Daniel Webster said this: He said, "If all of my possessions were taken from me with one exception, I would choose to keep the power of communication, for with it, I would regain all the rest." And that's why, of all of these incredible applications of FreeSpeech, the one that's closest to my heart still remains the ability for this to empower children with disabilities to be able to communicate, the power of communication, to get back all the rest.
Danijel Vebster je rekao ovo: "Kada bi mi oduzeli sve stvari, uz jedan izuzetak, odabrao bih da zadržim moć komunikacije, jer bih uz njenu pomoć vratio sve ostalo". Zbog toga, od svih neverovatnih primena FreeSpeech-a, meni je najdraža mogućnost da se da moć deci sa invaliditetom, da mogu da mogu da komuniciraju, moć komunikacije, kako bi mogli da vrate sve ostalo.
Thank you. (Applause) Thank you. (Applause) Thank you. Thank you. Thank you. (Applause) Thank you. Thank you. Thank you. (Applause)
Hvala vam. (Aplauz) Hvala vam. (Aplauz) Hvala vam. Hvala vam. (Aplauz) Hvala vam. Hvala. (Aplauz)