Pratique du Shadowing: Can This Robot Be My Personal Assistant - Apprendre l'anglais à l'oral avec la vidéo
Création de la leçon...
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I've always dreamt of having a robot and in 2026, it feels like that dream is a little bit closer all of the time.
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However, Very recently, it got much closer for me because on my desk, is this.
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This is a reachy mini.
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Now, reaching mini is a super cute robot from pollen robotics
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and hugging face and it's not just like a product toy robot that you buy.
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It's a straight up development platform that you could do anything you want with it.
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But just owning the robot wasn't really the dream.
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So I set out to connect Ricci Mini to Hermes and give myself a true robot personal assistant.
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And because I need to justify having a robot like this, I set out on a side quest as well.
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That side quest is to build
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from a cute little robot like this seems way more fun than practicing it with mom and dad.
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But before I even got here though, we needed to build Ricci because this thing comes unassembled.
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Now Ricci wasn't an easy build but it also wasn't a difficult build.
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It probably took an hour and 45 minutes and it could have taken much less if I was doing it by myself.
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This and learn what all of the different component connectors were.
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We got to learn how to use the screwdrivers and how to connect things.
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This isn't their first electronics project, but it definitely was their most involved.
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And when we finally got Ricci connected and turned on, there was moments of real genuine joy from them.
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Get behind him.
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We're private.
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Hi, Richie!
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Welcome to the city, marshmallow!
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You're a winner, marshmallow!
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So now that Ricci is built, it's time to get working on our custom software.
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Because we have a lot of things I would like to do with this.
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Now, the community -based apps are great, but I had bigger plans.
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So to make Ricci a true personal assistant and claim success here, I need this robot to do a few things.
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I need to, one, connect it to my Hermes.
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I need to get wake word detection so that way I can talk to it directly starting out of nowhere.
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I need to have conversation going back and forth.
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And as far as the personal assistant tasks go, I would love for this thing to have a memory.
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I would like for it to be able to do tool calling.
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I would like for it to do simple coding tasks, be able to use my home assistant.
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And I would love for this to be able to do personal assistant tasks like simply reading my calendar.
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A lot of those are very possible with Hermes, but many of these things are going to require true custom software.
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Now to give you some background, Ricci comes in two flavors.
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There is the light version, which is what we have here, which requires the brains of it to be running on a computer.
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I have a Mac mini right there that is perfect for running long running software on.
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So I'm going to be running all of my Ricci mini software off of this computer, and Ricci is going to be communicating over wifi.
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version of the Ricci Mini that has a built -in Raspberry Pi.
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However, I think the light version, if you have a long -running computer, makes a ton of sense, right?
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So what did I do?
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Well, I started off with a fork of the existing conversation app.
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From there, I used the prompt in the docs to really get started.
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I then replaced all of the calls to OpenAI with calls to my Hermes, which was really simple because Hermes has a great API.
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And this actually gave me a ton of I use my Hermes for a ton of stuff already.
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So just simply by connecting it to Hermes, I was able to get memory via honcho,
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tool calling of all the tools that my various profiles have set up, coding tasks so it can actually do coding on any of my machines since they're all connected via SSH.
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So simply getting those things working was super easy,
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but the tough stuff here was actually getting timing.
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Basically, the Ricci software has voice activity detection.
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It decides when speech is actually starting and ending based on the audio level that's coming in.
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If the voice activity detection detects speech or silence,
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it then starts to transcribe via the local SST, the speech to text that's done being whisper and it's happening on my Mac mini.
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From there, it looks to of this robot, my kids named it because just look at the guy.
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From then, Ricci would then acknowledge the conversation and then start conversation mode.
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Ricci basically just listens for the next sentence and then after 1 .1 seconds of silence,
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which by all means is a value that I am still tweaking
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and have had to tweak based on the way kids speak to this thing, the way I speak to this thing.
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It's taken a lot of trial and error here.
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It then transcribes that text locally.
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That text is basically sent to Hermes in a prompt.
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Hermes does its thing, returns the prompt.
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Then our software generates text to speech using Kokoro,
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to improve upon the general speed and latency in conversation with this thing.
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We then send that audio to the robot and the robot outputs it directly so we can hear it.
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It then begins listening for the next prompt for me.
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So what you can see is it's basically just a conversational prompt.
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Now we also have some stop word detection where we say go to sleep and Rigi will stop the conversation.
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Again, this is still things that I'm tweaking and I set out to create a whole host of where the latency is.
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Now, one of the reasons why Hermes is less good for this is because by default, Hermes agents have a ton of additional tokens in here.
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So the responses take a long time
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because we're sending a lot of information in each prompt rather than quick little fast prompts.
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It also depends, of course, which model you're using to have it respond to.
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Now, I just have this connected via my codec subscription.
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So it is using some chunky models rather than some highly tuned fast I will be experimenting with more in the future.
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So did this work?
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Well, let's start a wake listening and we're going to see
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if all of these things work and if we can check them off our list.
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I have Marshmallow here, we have wake word listening,
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we have conversation, and we're gonna first give this a try with memory and see if Marshmallow can understand.
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By the way, this is the custom UI that I've been building.
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Hey, Marshmallow.
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Hey, I'm listening.
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Oh What do you know about me?
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You're Scott.
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Oh You like concise, direct technical progress, live checks, and family -friendly Reiki mini -apps.
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You also prefer short robot prompts and you've got two kids who may use me for spelling practice.
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I am listening.
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Go to sleep.
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Okay, I'll listen for Hey Marshmallow.
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So, you can see that the conversation definitely works.
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Now, the latency is certainly there.
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It's something that I'm working on improving.
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Okay, now let's try some of the other things we had in mind.
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Now, I have several different profiles in Hermes that all have different abilities.
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And the marshmallow profile is kid friendly and kids safe.
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However, I have a default profile that has access to things like my calendar, as well as can do coding.
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new conversation.
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What's on my calendar for today?
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Woohoo!
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Jury duty all day, drop off from 8 :00 to 8 :30 a .m.
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Release phases tomorrow from 6 :00 to 7 :00, 0 :00 PM.
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Change the color of the Marshmallow Conversation app background to be pink.
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Mm -hmm.
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Now the coding tasks may take just a second here since it's going off
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and I don't think this is even inside of the project
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so it's probably going to have to go look for the project on my machine and then change those files.
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Done, the Marshmallow Conversation app now has a pink background, and I verified it live at port 7860.
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It looks good.
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Yeah, it looks good.
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Marshmallow, can you turn all of the lights off please?
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Mm -hmm.
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you you
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all reachable lights are off so now
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that i have the personal assistant of my dreams it's time to get working on the hard part
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which is the spelling test now the spelling test has a
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number of features it needs to ingest the spelling list of
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words it needs to use them in a sentence it needs user has gotten the spelling incorrect.
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Now, there's a ton of small little problems here and it's time to get to work.
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So after grinding on our spelling test for quite a while, we have something that can work that allows us to even save and restore various spelling lists.
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Now is the moment of truth.
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We're going to be giving this spelling test to my 9 year old and see how he does.
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J -U -M -P.
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The word is jump.
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It is spelled J -U -M -P, try spelling it with me i'm so mad okay
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so the reviews were not glowing he was a harsh customer
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and he didn't like it this is certainly not going to help him practice spelling
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but i have some ideas on how to fix this what
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if instead of having a back and forth that took
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so long we pre -rendered all of the audio
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and including pre -rendering any of the helpful text any of the words that's saying you almost got it
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going to feel snappier back and forth.
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And what if we also output the letters on the screen as he was saying it?
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But most importantly, what if it actually worked?
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Because as you saw, and honestly, what you didn't see was him spelling the words correctly over and over again, and the robot consistently getting them wrong,
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specifically because the window for when he was supposed to son a fan of this app.
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So because of this first initial failed test, what I actually ended up doing was setting the Ricci mini in front of a computer,
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having that computer take the spelling test on the Ricci mini back and forth with audio and microphones.
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And then that way, the system was able to self heal
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and improve the latency using open AI models to run the tests check the debugging information
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and then fix it test it reiterate until now we have an app that is i gotta say working pretty well
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Your word is robot.
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The teacher asked us to spell robot.
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Um, R -O -B -O -T.
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Nice work, you spelled it carefully.
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Huh.
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Your word is eat.
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The teacher asked us to spell eat.
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EAT.
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Nice work, you spelled it carefully.
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Your word is jump.
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The class practiced the word jump today.
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J U M P.
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Nice work.
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You spelled it carefully.
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So I think this was a great success.
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The robot is now my personal assistant.
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It's taking spelling tests with our kids,
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and it's only going to get better from here because I still haven't really implemented that much with the camera.
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The next step on the docket is to use the camera to teach my son and I how to play Warhammer 40k.
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We're going to use the camera and the LLM that this is talking to,
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to discuss both strategy, what to do next so that way it can even identify pieces on the battlefield.
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That is a big project and the one that I'm going to be diving into next.
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That said, I'm a huge fan of this little robot.
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It's a really cool open project that you can do all kinds of stuff with and I gotta say, I think I just made a new friend.
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Vocabulaire et conseils d’expression pour cette leçon
Cette vidéo contient 166 phrases et 2015 mots à répéter en shadowing. La partie parlée dure 13:48. Le locuteur parle à un rythme régulier d’environ 146 mots par minute, confortable pour le shadowing. Seuls 81 % des mots font partie des 3 000 mots les plus courants en anglais, le vocabulaire est donc exigeant.
Vocabulaire clé de cette vidéo
15 mots moins courants de la vidéo, avec leur prononciation et leur sens :
- robot /ˈɹoʊ.bɑt/ (nom) — robot. An intelligent mechanical being designed to look like a human or other creature, and usually made from metal.
- spelling /ˈspɛl.ɪŋ/ (nom) — orthographe. The act, practice, ability, or subject of forming words with letters, or of reading the letters of words; orthography.
- prompt /pɹɑmpt/ (verbe) — inciter. To lead (someone) toward what they should say or do.
- connect /kəˈnɛkt/ (verbe) — accoupler, connecter. To join (to another object): to attach, or to be intended to attach or capable of attaching, to another object.
- spell /spɛl/ (nom) — charme, maléfice. Words or a formula supposed to have magical powers.
- audio /ˈɔ.di.oʊ/ (adjectif) — audio. Focused on audible sound, as opposed to sight.
- detection /dɪˈtɛk.ʃən/ (nom) — détection. The act or process of detecting, uncovering, or finding out, the discovery of something new, hidden, or disguised.
- carefully /ˈkɛɹf(ə)li/ (adverbe) — soigneusement. With care; attentively, circumspectly.
- custom /ˈkʌstəm/ (nom) — coutume. Frequent repetition of the same behavior; way of behavior common to many; ordinary manner; habitual practice; method of doing, living or behaving.
- calendar /ˈkæl.ən.də/ (nom) — calendrier. Any system by which time is divided into days, weeks, months, and years.
- silence /ˈsaɪ̯ləns/ (nom) — silence. The absence of any sound.
- output /ˈaʊtpʊt/ (nom) — sortie. Production; quantity produced, created, or completed.
- default /dɪˈfɔlt/ (nom) — défaut, non-respect. The condition of failing to meet an obligation.
- quest /kwɛst/ (nom) — quête. A journey or effort in pursuit of a goal (often lengthy, ambitious, or fervent); a mission.
- render /ˈɹɛn.dɚ/ (verbe) — rendre. To cause to become.
Les verbes à particule que vous entendrez
- end up (verbe) — se terminer, se finir. To bring to a conclusion.
- go back (verbe) — rentrer, retourner. To return to a place or state after having been there at a previous time.
- go off (verbe) — exploser. To explode.
- look at (verbe) — regarder. To observe or watch.
- look for (verbe) — chercher, rechercher. To seek.
- set up /ˌsɛt ˈʌp/ (verbe) — mettre en place, installer. To make ready for use.
- turn on (verbe) — ouvrir. To set a flow of fluid or gas running by rotating a tap or valve.
Prononciation à surveiller
Le locuteur utilise 32 contractions et formes réduites, comme I'm, we're, wasn't. Prononcez-les sous leur forme courte, telles que vous les entendez.
- Les sons « sh » et « zh »: detection /dɪˈtɛk.ʃən/, harsh /ˈhɑɹʃ/, subscription /səbˈskɹɪpʃən/, marshmallow /ˈmɑɹʃˌmɛl.oʊ/, conversational /ˌkɒnvə(ɹ)ˈseɪʃənəl/
- Mots longs — placez bien l’accent: experiment /ɪkˈspɛɹ.ə.mənt/, consistently /kənˈsɪstəntli/, communicate /kəˈmjuːnɪkeɪt/, electronics /ɪˌlɛkˈtɹɑ.nɪks/, importantly /ɪmˈpɔɹ.tənt.li/
Comment s’entraîner avec cette vidéo
- Écoutez la vidéo en entier une fois sans parler et notez les mots que vous ne connaissez pas.
- Répétez phrase par phrase à vitesse normale, en reprenant chacune jusqu’à ce que votre rythme corresponde à celui du locuteur.
- Enregistrez-vous et comparez avec l’original, en faisant attention à des mots comme robot, spelling, prompt.
La grammaire de cette vidéo
Les structures que le locuteur utilise le plus, avec les mots exacts de la vidéo :
| Structure | Dans la vidéo |
|---|---|
| Present perfect have/has + participe passé — une action passée qui compte encore maintenant | I've always dreamt · have set · has gotten |
| Propositions relatives who / which + proposition — une précision sur une personne ou une chose | version, which is · Hermes, which was · kids who may |
| Voix passive be + participe passé — l’accent est mis sur ce qui arrive, pas sur qui le fait | is built · is spelled |
Qu'est-ce que la technique du Shadowing ?
Le Shadowing est une technique d'apprentissage des langues fondée sur la science, développée à l'origine pour la formation des interprètes professionnels. Le principe est simple mais puissant : vous écoutez de l'anglais natif et le répétez immédiatement à voix haute — comme une ombre suivant le locuteur avec un décalage de 1 à 2 secondes. Les recherches montrent une amélioration significative de la précision de la prononciation, de l'intonation, du rythme, des liaisons, de la compréhension orale et de la fluidité.