ฝึกพูดภาษาอังกฤษด้วยเทคนิค Shadowing จากวิดีโอ: 3 Ways AI Will Completely Change Your Life by 2029
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Look around us right now in 2026.
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Artificial intelligence is growing faster than ever before.
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Every single month, a new AI model comes out.
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Every week, there's a new feature like making real -looking videos, writing tough computer code, or speaking in perfect human voices.
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Because things are moving so fast, people mostly think the future of AI will just keep going up in a straight line.
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They think AI will always get bigger, faster, and smarter every single day.
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But if you ask computer engineers, scientists and electricity experts, they will tell you something very different.
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The future of AI is not a straight line.
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Between now and 2029, our world is standing at a giant turning point.
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Depending on how tech, electricity, power grids and human laws clash with each other, our future could go in three totally different directions.
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Now, before we look at how your daily life will change, here are the three big outcomes we are heading towards.
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Outcome 1 will be the super leap, where AI solves huge software and medical problems, doing full jobs all by itself like a digital worker.
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Outcome 2 will be the power wall, where AI runs out of physical electricity and computer parts,
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forcing the whole tech industry to slow down and rebuild.
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And outcome 3 is going to be the trust break, where making fake videos and audio become so cheap and easy that the internet breaks,
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changing our security jobs and laws forever.
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In each of these situations, the job market and the global economy will change in very different ways.
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Let's step into each of these three worlds so you can see what your life and career will actually look by 2029.
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Let's start with outcome 1, the super leap.
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This is the positive future where computer scientists fix all the AI's main problems very fast.
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In 2027, the way we use computer changes forever.
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Right now, you sit down and type questions into the chat box and the AI gives you the answer.
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But in the future, the chat box goes away.
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Instead, we use agent teams, groups of AI tools that work together nonstop.
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Like imagine you want to start a business.
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You do not write the code or build the website yourself.
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You simply tell an AI build a full food delivery app, add a payment system, test it for security bugs and launch it.
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The main AI breaks this big task into 20 smaller jobs.
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One AI writes the code, another designs the screen, another checks for error and another fixes the bug.
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You go to sleep.
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And when you wake up in the morning, your full software product is built and live on the internet.
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By 2028, this massive computer power leaves the screen and enters the real world.
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In science, finding a new life -saving medicine used to take 10 to 15 years of hard lab work.
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Under the super leap, AI can test millions of chemicals, mix on a computer every single minute.
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Scientists can see how chemicals react before even touching a real glass test tube.
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This gives us new medicines and better materials for solar panels in just months instead of decades.
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And by 2029, AI is all around you, invisible and smooth.
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You might wear light smart glasses or simple wireless earbuds.
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The AI listens to what you hear and sees what you see.
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It remembers every meeting you ever had, reminds you of a person's name when you forgot, warns you about your health before you feel sick,
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and manages your daily schedule.
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So in this big leap, this can be the world in next three years.
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In this world, the job market shifts from doing the work to managing the work.
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Companies no longer hire 10 junior software developers or designers.
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Instead, they hire one single AI director who manages a team of AI workers.
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We can see people building billion -dollar companies all by themselves.
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The world economy grows super fast because making digital thing cost almost zero.
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But there is a big risk.
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If a major AI internet network goes offline, all global businesses stop instantly.
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Now let's look at outcome 2, the power wall.
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What happens if AI development slows down?
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Not because the software is bad, but because we ran out of physical electricity.
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Right now, running giant AI system takes a massive amount of electricity.
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Data centers filled with thousands of computer chips use as much power as a small country.
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So now let's see the next three years in this era.
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By 2027, tech companies hit a physical wall.
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To build the next big AI model, companies need huge amount of power.
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But local electricity grids cannot give that much amount of power without causing blackout for normal homes.
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At the same time, factories cannot make advanced chips fast enough and data centers run out of water to cool their machines.
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The fast release of huge new AI suddenly stops.
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And by 2028, businesses fall into what experts call it the 80 -20 trap.
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Company realize that while AI can do 80 % of the job very fast, getting that final 20 % perfectly right without mistake is extremely hard.
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So for reference, if an AI writes an article, a human still has to check it.
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If an AI handles legal papers or medical records, a human expert must carefully read every single line to prevent dangerous mistakes.
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Because hiring human experts to check AI work is costly, companies realize AI does not save as much money as they originally thought.
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And by 2029, the entire tech industry changes its goal.
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Companies give up on building giant expensive AI systems that eat massive amount of electricity.
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Instead, they focus on making things highly efficient.
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They make tiny super fast AI models that run directly on your mobile phones or laptop without needing an internet connection.
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In this world, AI stop feeling like the world -changing science fiction movie and become a simple, helpful daily tool just like electricity or Wi -Fi.
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And what about the job market and economy in this world?
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Experienced human professionals become more valuable than ever because AI cannot be trusted 100%.
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Jobs for skilled humans, checkers, senior engineers, lawyers, and healthcare workers are very safe and high -paying.
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The economic boom moves away from pure software and shifts into physical industries, electricity grades, nuclear energy, chip making, and green power.
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The economy grows at a normal steady pace and businesses use a balanced mix of human experts and local AI tools.
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Finally, we have outcome 3, the trust break.
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What happens if AI moves faster than human society laws and security just can't handle it?
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To understand why this scenario is so real, just look at what is happening right now, today.
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Criminals are using short audio clips from social media to copy people's voices in just three seconds.
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In this real world scammers have used fake video calls of
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company bosses to trick employees into sending millions of dollars like there were many news around i've seen
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so what will happen if this continues
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and what will be the world in three years
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so by 2027 making super real fake videos fake voice calls
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and fake photo cost almost zero money anyone with a basic computer can download free AI tools
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and make a real looking video of anyone on earth saying or doing anything.
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When fake content becomes that cheap and instant, the internet faces a crisis called the dead internet.
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You can no longer trust a video or social media, a news report, or even a phone call from a friend or family member.
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Scammers use automated voice bots to call thousands of people at once, copying their relatives' voices to ask for emergency money.
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Now, because trust is broken, governments are forced to pass strict new laws.
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Like by 2027, every camera, phone, or news agency must use secure digital stamps inside their devices.
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This is to prove that the video or photo was taken by a real camera lens and was not made by AI.
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And by 2028, office jobs face huge problems.
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Simple starting jobs like basic data entry, basic computer coding, customer service chats and filing papers are taken over by AI very quickly.
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Colleges and governments training programs struggle to train millions of young workers fast enough.
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This creates a big gap between old -style workers and people who know how to manage AI tools.
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And by 2029, countries enter an AI cold war.
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Government decides that advanced AI models are dangerous national security tools.
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The United States, Europe, and Asia put strict bans on sharing advanced chips, computer hardware, and code.
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Instead of one open global internet, the digital world splits into closed, heavily guarded national networks.
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Now, obviously, in this era, we have to talk about the job market and economy as well.
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The job market sees a massive shake -up, like entry -level office jobs disappear rapidly,
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making it hard for fresh college graduates to start traditional corporate careers.
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But at the same time, new high -demand jobs open up, like cybersecurity security expert, digital fraud checker, hardware tester, and identity protection agent,
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the world economy becomes heavily protected by national borders.
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Taxes on tech items will rise initially
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and businesses have to spend billions of dollars on security and legal approval just to run safely.
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So now you know all the three outcomes.
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But the question is which of these three outcomes will actually happen by 2029?
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The truth is, the real future will not be 100 % of just one timeline.
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Instead, our world will be a mix of all three.
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We will experience the amazing scientific and medical breakthroughs from the super leap that was the first world we created,
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the real world electricity problem from the second world that was the power wall,
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and the digital security challenges from the third world that was the trust break.
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And no matter which outcome takes the lead, two things are clear.
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Your job will require managing AI, not just competing with it.
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Real economic values will belong to people who can solve real world problems and check if information is actually legitimate.
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And if I talk about the main lesson, it's simple.
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Tech itself is neutral.
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But how we prepare for it makes all the difference.
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The people who succeed in 2029 will not be the ones who ignore AI
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and they won't be the ones who blindly trust everything they see on the screen.
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The winners will be the people who learn how to manage AI tools,
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check real information, and adapt as the world changes because adaptation is the biggest thing.
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Now according to you which outcome do you think is most likely to happen over the next three years?
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Are we heading for the super leap, the power wall or the trust break?
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Drop your thoughts in the comment below, hit the like button if you enjoy the breakdown and subscribe
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so you don't miss out next deep dive into the future of technology.
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So this is Akash Fiyas, you are watching Sharian CI School.
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Till then, bye -bye.
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คำศัพท์และข้อสังเกตด้านการพูดสำหรับบทเรียนนี้
บทเรียนฝึกพูดนี้ใช้วิดีโอ “3 Ways AI Will Completely Change Your Life by 2029” เป็นสื่อ คำที่ถูกพูดซ้ำบ่อยที่สุด: outcome, computer, electricity, super, fast วิดีโอนี้มี 130 ประโยค และ 1839 คำ สำหรับฝึกพูดตาม ช่วงที่มีเสียงพูดยาว 10:26 ผู้พูดพูดด้วยความเร็วเป็นธรรมชาติ ประมาณ 176 คำต่อนาที ใกล้เคียงกับบทสนทนาในชีวิตประจำวัน 85% ของคำอยู่ใน 3,000 คำที่ใช้บ่อยที่สุดในภาษาอังกฤษ ส่วนที่เหลือควรดูไว้ก่อนเริ่มฝึก
คำศัพท์สำคัญในวิดีโอนี้
คำที่ควรเรียนรู้ 15 คำจากวิดีโอ พร้อมคำอ่านและความหมาย:
| คำศัพท์ | คำอ่าน | ความหมาย |
|---|---|---|
| leap คำกริยา | /ˈliːp/ | เผ่น |
| hire คำกริยา | /ˈhaɪɹ/ | จ้าง |
| scientist คำนาม | /ˈsaɪəntəst/ | นักวิทยาศาสตร์ |
| solve คำกริยา | /sɒlv/ | แก้, แก้ไข |
| hardware คำนาม | /ˈhɑɹdˌwɛɹ/ | ฮาร์ดแวร์ |
| grid คำนาม | /ɡɹɪd/ | ตาราง |
| ignore คำกริยา | /ɪɡˈnɔː/ | เมิน |
| relative คำนาม | /ˈɹɛl.ə.tɪv/ | ญาติ, ญาติพี่น้อง |
| lesson คำนาม | /ˈlɛs.ən/ | บทเรียน |
| worker คำนาม | /ˈwɝ.kɚ/ | คนงาน, กรรมกร |
| designer คำนาม | /dɪˈzaɪnɚ/ | ผู้ออกแบบ, นักออกแบบ |
| compete คำกริยา | /kəmˈpiːt/ | แข่ง, แข่งขัน |
| fraud คำนาม | /ˈfɹɔːd/ | การฉ้อโกง, การโกง |
| remind คำกริยา | /ɹəˈmaɪnd/ | เตือน |
| tube คำนาม | /tuːb/ | หลอด |
กริยาวลีที่คุณจะได้ยิน
| คำศัพท์ | ความหมาย |
|---|---|
| sit down คำกริยา | นั่ง |
ไวยากรณ์ในวิดีโอนี้
โครงสร้างที่ผู้พูดใช้บ่อยที่สุด พร้อมคำพูดจริงจากวิดีโอ:
| โครงสร้าง | ในวิดีโอ |
|---|---|
| Passive voice be + กริยาช่อง 3 — เน้นสิ่งที่เกิดขึ้น ไม่ใช่ผู้กระทำ | is built · cannot be trusted · is broken |
| Relative clauses who / which + อนุประโยค — ข้อมูลเพิ่มเติมเกี่ยวกับคนหรือสิ่งของ | people who know · people who can · people who succeed |
การออกเสียงที่ควรระวัง
ผู้พูดใช้รูปย่อและรูปลดเสียง 4 ครั้ง เช่น can't, don't, I've ให้พูดแบบสั้นตามที่ได้ยิน
- เสียง “th”: smooth /smuːð/, breakthrough /ˈbɹeɪk.θɹuː/
- เสียง “sh” และ “zh”: fiction /ˈfɪkʃən/, efficient /ɪˈfɪʃənt/, shake /ˈʃeɪk/, artificial /ˌɑː.tɪˈfɪʃ.əl/, adaptation /ˌæd.æpˈteɪ.ʃən/
- คำยาว — ลงเสียงหนักให้ถูกพยางค์: electricity /ɪˌlɛkˈtɹɪsɪti/, artificial /ˌɑː.tɪˈfɪʃ.əl/, legitimate /lɪˈd͡ʒɪt.ɪ.mət/, developer /dɪˈvɛləpɚ/, invisible /ɪnˈvɪzəb(ə)l/
เสียงที่คนไทยมักออกเสียงยาก:
- เสียงท้ายคำ — ออกเสียงให้ครบ ไม่เปลี่ยนเป็นตัวสะกดแบบไทย: solve /sɒlv/, relative /ˈɹɛl.ə.tɪv/, skill /skɪl/, pace /peɪs/, artificial /ˌɑː.tɪˈfɪʃ.əl/
- /v/ — ไม่ใช่ /w/ ให้ฟันบนแตะริมฝีปากล่าง: solve /sɒlv/, relative /ˈɹɛl.ə.tɪv/, developer /dɪˈvɛləpɚ/, dive /daɪv/, invisible /ɪnˈvɪzəb(ə)l/
- /z/ — เสียงก้อง ไม่ใช่ /s/: designer /dɪˈzaɪnɚ/, lens /lɛnz/, invisible /ɪnˈvɪzəb(ə)l/
วิธีฝึกกับวิดีโอนี้
- ฟังวิดีโอให้จบหนึ่งรอบโดยยังไม่ต้องพูด แล้วจดคำที่ยังไม่รู้จัก
- เริ่มที่ความเร็ว 0.75× พูดตามทีละประโยค แล้วกลับไปใช้ความเร็วปกติเมื่อเริ่มคล่อง
- อัดเสียงตัวเองแล้วเทียบกับต้นฉบับ โดยสังเกตคำอย่าง leap, hire, scientist เป็นพิเศษ
เทคนิค Shadowing คืออะไร?
Shadowing เป็นเทคนิคการเรียนรู้ภาษาที่ได้รับการรับรองทางวิทยาศาสตร์ พัฒนาขึ้นสำหรับการฝึกนักแปลมืออาชีพ วิธีการนี้เรียบง่ายแต่ทรงพลัง: คุณฟังเสียงภาษาอังกฤษจากเจ้าของภาษาและพูดตามทันที — เหมือนเงาที่ตามผู้พูดด้วยช่วงเวลาห่าง 1-2 วินาที การวิจัยแสดงว่าเทคนิคนี้ปรับปรุงความแม่นยำในการออกเสียง ทำนองเสียง จังหวะ การเชื่อมเสียง การฟังเข้าใจ และความคล่องแคล่วในการพูดได้อย่างมีนัยสำคัญ