La TECNOLOGIA renderà OBSOLETO imparare le lingue?

Will artificial intelligence make language learning obsolete? If in ten

years we will have a device that will allow us to communicate with people who speak other languages

efficiently and without obstacles, will there still be people who will learn languages? This is

a question that I often ask myself, which leads me to have existential crises because I think: "Oh my god,

in ten years my work will no longer make sense! Nobody will learn Italian!" Now,

no one can know how things are going to go, but I discussed it with my dad in my last episode

of the podcast and why with my dad, why my dad (who just retired)

has been involved with his entire career in intelligence. artificial and specifically

voice recognition. You know when you talk to your devices, if you do?

(automatic voice) In English it is "subscribe to Italian podcasts". Now

I can act as an interpreter in a foreign language.

Q: Hi, how are you doing?

A: Hi, how are you? D: I'm fine, and you?

A: I'm fine, and you? Q: I'm fine because I

haven't signed up for Podcast Italiano yet. A: I'm sick because I haven't

subscribed to an italian podcast yet. Q: What's an italian podcast? Do you mean 'Podcast

Italiano', by any chance?

A: What is an Italian podcast? Do you mean by any chance 'Italian Podcast'?

D: Yes, of course, Italian Podcast, on YouTube! A: Yes, of course italian podcast on youtube.

D: Of course, but do you know there's a podcast version of it as well?

A: Sure, but did you know that there is also a podcast version?

This technology already exists, maybe it's not perfect but in ten years? I do n't

know ... Anyway my father was involved in speech recognition, that is the part

of understanding by the human language machine. We did two episodes,

the first about his career in the world of artificial intelligence and the

second specifically about the linguistic applications of artificial intelligence

and neural networks, which are so fashionable today. I leave you now an excerpt from the

second episode in which we talk about these things. I hope you like it.

Q: I wanted to talk now a little bit about the ... artificial intelligence in the linguistic

field , so it seems to me that there are three uses mainly: translation,

voice recognition and voice synthesis, so to make a machine speak, right ?

A: Exactly. Q: Here,

I wanted to start with the very speech recognition you've been dealing with for a

long time and ask you how it works. You told me that once upon a time they just put linguistic

knowledge in the machine and then this approach was completely abandoned.

A: Exactly. Until, let's say, all the 90s, until 2000 even the automatic recognition

systems had the skills of human experts inside. There was, for example, the phonetic knowledge

of the language, that is, what are the basic sounds of the language and how they are organized among

them; lexical knowledge, that is, how these sounds form words; then there was the

syntactic knowledge, that is how words form correct sentences of the language, and these ...

these knowledge were introduced by human experts, by phoneticians, linguists

who inserted into the code (or in any case in the knowledge of the computer ) these informations.

D: That is, in short, all the grammar of a language because it is grammar ...

A: Yes, we spoke, in fact, of grammar, even the grammars of a language

were inserted into ... into the computer. Q: So there were people with a

grammar book that translated rules into computer instructions?

A: Yes yes, exactly. At the beginning I myself had brought Italian grammar to the office.

D: Of Serianni? A: The one I had in high school, I don't know whose it was,

but and this went on for a very long time, then they ... they started using

statistical methods too, at least for the lower level part of the sound. . But then lately,

so I would say from 2013 onwards all this has literally disappeared, in the sense that

models of neural networks called end to end models have arrived , i.e. models that go from start to

finish, and these models in speech recognition start from signal that comes out of the microphone, from

the waveform and reaches the words. Then a waveform enters, a sequence of words comes out.

D: And so ... so everything in between, syntax, phonetics, morphology, vocabulary, everything ...

everything in between happens magically? A: It happens magically in the interaction between these

neurons. These end-to-end models are even more complicated than I have described

neural networks . And yet all these ... this human knowledge and linguistic knowledge have disappeared.

Oh my God, maybe they are present in the neural network but it is an opaque model, it is a so-called

black box, it is a black box and therefore we do not know if the neural network has used them, has

not used them. Will he have ... in his learning he will have rediscovered phonetics, will he have rediscovered

linguistics? We don't really know. Q: So there is no way to understand what he is

learning and what he "thinks", in quotation marks? A: No, I would say ... I would say no. This is

perhaps one of the limitations of these neural networks that ... which perhaps is also a limitation of

biological neural networks , in the sense that they are not inspectable. D: So they're not ... they're not very transparent.

And so the only thing you need for these models

is audio that is transcribed, right? A: Transcribed into words. And it takes

many hours, we are talking about thousands of hours of transcribed recordings and the more there is, the

better it will work. But it also takes days and days of very powerful computer computing

to train the neural network, but eventually this network begins to figure out how to relate

this strange input coming out of the microphone with words. In the case of recognition;

in the case of translation it correlates the words in one language with the words in the other, even with

totally different characters, this does not matter. D: Sure. And instead in the case of synthesis,

that is, making the machine speak, how does that work? The correlation between what is it?

A: Yes, it is exactly the other way around. The examples are pairs where the input is a sequence

of words and the output is a waveform. Q: But is the ... waveform created from scratch?

A: From scratch. D: Because once upon a time,

perhaps you told me, they used just blocks of words, bits of

words that were recombined in various ways. A: Exactly, what was in the synthesis,

let's say, the classic one with knowledge introduced by man in which, in fact, man classified

many pieces of recording that were then concatenated, the so-called concatenative synthesis.

D: What can still be heard, for example, on some trains ...

A: Otherwise, but I would say that ... D: Is it still used a lot?

A: Yes yes yes, in the Italian railway systems the synthesis is still that of

the 90 '. In my opinion or Amazon's systems they are already used though.

Q: So if we have a system that ... the first step is to recognize the voice, then from the sound to the

text, then the translation that translates into another language, into another text then, translated,

and then we have the synthesis that he reads the translation aloud, in fact we have ... we have an

interpreter, we have an interpreter. So you think that maybe translators and interpreters, translators

already now but interpreters in the future, will be at risk, for example, in conferences?

A: Unfortunately for human translators and interpreters I think yes, it will happen,

or at least it will greatly reduce the scope ... the possibilities of ... work. In the sense that the

sooner things will disappear more, let's say, more routine. I believe that the translation of technical manuals

or product manuals is already done almost entirely automatically, even though there are still some

errors inside. And then gradually also the work of interpreting maybe ... Maybe the two alternatives will exist

for some time, the automatic one, cheaper and less precise, and

the human one, more accurate and more expensive. D: And I think that even now it is starting to be

a problem for some, for some translators, perhaps because clearly if

the translator only has to correct the work done by a machine the pay,

the pay will be ... it will be lower. A: Of course, and perhaps even less beautiful work.

D: But even less beautiful yes. Going back to the topic of languages, do you think that learning languages

will still be relevant in 10 or 15 years? This is a question I often ask myself. I don't know if there will be

a device that will allow us to communicate with people who speak different languages ​​or a

chip in the brain but also something less futuristic, let's say. Will it still be relevant?

A: But I think that at least for a long time it will not become obsolete, in the sense that one learns

a language for many reasons, but surely one thing is to be able to speak and communicate in a language

without any device, another thing is to always have a device in hand or a device

that acts as a mediator. I imagine that for reasons or work, or tourism, or even a little

occasional these devices will certainly be used. Or maybe even in certain conferences which

are occasional meetings of people of different ... so many nationalities could be used. But if

one wants, in fact, to learn a language also to enter the culture of a nation, of a country

this will remain totally irreplaceable, unless, as you mentioned, to implant

artificial neural networks in the brain, then they implant the memory expansion of the language,

you buy it and they bring it to you, but this really in my opinion is a little too far.

And this was the excerpt, I hope you enjoyed it. If you want to hear the whole episode or the

two episodes we did find the link below. Oh and if you didn't know,

yes I have a podcast for those who learn the Italian language and that's why my name is Italian podcast,

I know it's a bit weird. But I think these episodes in particular can be of interest to everyone

even if you are Italian, because in short, my father is an expert in the sector. So let me

know what you think, would you learn a language if there was a technology like it already

exists but much more efficient than this? Maybe integrated into a device in our brain,

or into a device that I know, a little more efficient than a mobile phone,

which still acts as a bit of an obstacle, gets in the way between me and another person? Or do

you think that you will continue to learn the language perhaps out of love for a culture or because you

like learning languages? And what do you think most people will do? Let me

know what you think as you understand it didn't have a real video for this week but

let's be back next week with our usual schedule. Until next time! Bye Bye.