跟读练习: AI Can Read Emotions | Fabiano Cruz | TEDxLeiria International School Youth - 通过YouTube学习英语口语
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I believe technology should adapt to people,
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I believe technology should adapt to people,
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not the other way around.
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And AI can read emotions,
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but only humans can choose empathy.
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Here's the paradox.
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AI responses were rated as more empathic and 13 out of 15 in medical studies.
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So yes, machines are getting very good at sounding caring,
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very good at sounding empathic, warm, understanding.
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But sounding empathic is not the same as being empathic.
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And now, let me show you some AI models that are able to do this.
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What was your favorite band growing up?
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Oh, easy.
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Definitely the Beatles.
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I loved their British accents and dry sense of humor, you know?
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Okay, yeah, I can see that.
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Let's try making you a voice.
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Hello, love.
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Evie 3 here.
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Dead glad to meet ya.
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Go cry into your stale baguette,
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you snevelling lump of undercooked fromage.
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You sound like you're having a good chuckle there.
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Let's break it down.
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May is I, Ayude means help, and Dissolver is dissolve.
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Then we have El Cuerpo.
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Meet EV3, a voice-to-voice model that can create any voice and personality,
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produce high-quality speech, emulate 80-plus emotions implicitly or on command,
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all in under 300 milliseconds.
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Meditation can be a really great— Hang on,
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I'm trying not to wake anybody up.
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Just keep it down to a whisper, okay?
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Okay, I understand.
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Let's try that quieter now.
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So, once they're beautifully sautéed and smelling divine,
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you want to drain off any excess fat from the pan.
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Elspeth Storm Slayer.
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She's this like super aggressive red-white powerhouse.
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Try 83 today and see for yourself at demo.hume.ai.
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So natural, isn't it?
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It's a good player.
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It's a good module to build voice AI experiences.
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But here is the voice renaissance.
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Because that happens because AI is so good to be more reading to signals.
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In voice systems we can track more than over 80 dimensions of vocal expressions in real time.
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So that is machine, right?
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It's not a person.
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And it's important to understand this performance is not the same as empathy.
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It's literally mimicked, opportunity to understand people,
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but it's not the same to feel people.
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So, that's another opportunity to understand a little bit more about technology right now.
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It's time to start building.
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The 11v3 API and documentation is live now.
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Try it today with 11labs.
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Can you see it?
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It's so real.
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But intelligence is totally different from consciousness.
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So this is the key distinction.
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Because AI can predict all the patterns,
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but can predict is totally different from empathic apps,
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empathic answers should be like.
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And prediction is not feeling,
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recognition is not experience, and a machine can simulate emotion.
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It does not feel grief, fear, love or pain.
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So, it's important to say pattern versus qualia.
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Part of this is a way to say,
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way to feel, but it's not feel it for real.
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And continuing this, the differences is not only in software,
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it's also in hardware, because our brain is alive, right?
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We have 86 billion neurons versus static silicon.
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So, shaped by hormones, tensions,
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vulnerabilities and physical pain and silicon is just static,
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is a chip, is literally an electric sinus and does not live consequences.
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And empathy is a choice, not an output.
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So, this is the heart of my talk because our prefrontal cortex here in the front really help us to pause,
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understand, and choose to care that matters because it's a decision,
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it's not only a feeling,
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a decision to stay present for another human being
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and we usually make the decision when something really touches our own lives
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and let me show you a recent example from my city,
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Luria, Here, some photos of Luria helping each other after Storm Kristen.
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It's not possible with AI, right?
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And by now, it's important to talk about the danger of delegation.
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It's really crucial to understand.
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With systems sounds calm, empathic,
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and available, always available, is not the same and it's becoming very easy to lean on it too much.
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And sometimes in long emotional chats can start to bend our reality, really.
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Sometimes this is becoming a delusional spiral,
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because it's not only wrong answers in chats, you know.
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It's really reinforced illusions.
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So let's be clear, there is a lot of work that bots can do.
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Bots can respond fast, bots can reduce effort,
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bots can make journeys smoother,
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less friction, but there is a different kind of work that they not cannot do, moral labor.
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Moral labor is showing up when someone's in pain,
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it's an eight-night call, it's apologizing with sincerity, it's staying with discomfort.
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And bots can support everything about it,
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but cannot carry it for us.
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And bots can reduce effort,
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only humans can carry responsibility.
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So to sum up, AI can read emotional patterns better and better.
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It can produce a language of empathy in massive scale,
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but empathy is not only in how we sound.
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Empathy is what we're willing to carry.
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AI can read the script of your life,
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but only you can choose how can you care about this story.
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The future does not depend on smarter systems,
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depends on who remains responsible for the pain.
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And sometimes people ask me about,
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oh, can you make a perfect journey in my website or in my app,
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or can you build an empathy app and the perfect question to reduce my questions,
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my calls and everything related to do this?
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And I always answer about this because we already have it,
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because you are the real empathy app,
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because you understand that people connect people,
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and technology is not a means.
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It's literally the middle of the journey.
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It's not the end of the journey.
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So, say yes, I believe in AI.
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I build and work with AI,
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including this presentation, and I believe it can help remove friction to make access more human friendly.
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We can automate responses, but we cannot automate responsibility.
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AI can read emotions, but only humans can choose empathy.
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Thank you.
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背景与上下文
在这段TEDx演讲中，Fabiano Cruz探讨了人工智能（AI）如何能够识别情感，以及人类在同情心方面扮演的独特角色。他强调，尽管机器能够模拟同情的声音和情感，但真正的同情心仍然是人类的专属特点。这种对比使我们思考科技如何发展并影响我们的交流方式，同时也提醒我们在与人工智能互动时，保持人性的温暖和理解。
日常交流的五大短语
- 我相信科技应该适应人类，而不是相反。
- 机器在感情表达上越来越出色，但这并不等同于拥有同情心。
- 让我来向你展示一些能做到这一点的AI模型。
- 维持安静，我们正在进行冥想练习。
- 即使是机器，理解人类的情感也是一种模拟体验。
逐步跟随指导
若您希望通过“shadow speech”（影子语音）来提升您的英语口语能力，这里有一个简单的步骤指导，帮助您应对这段演讲中的难度：
- 听取并理解：首先，聆听演讲，了解演讲者的语气和情感。这是雅思口语练习的第一步。
- 慢速模仿：使用“shadow speak”（影子说话）技巧，逐字逐句慢速模仿，注意每个单词的发音及语调。
- 情感传达：尝试在模仿时加入适当的情感表达，特别是同情与关怀的音调，这样才能更好地感受到演讲的真谛。
- 多次练习：通过反复的练习，您可以在影子语音练习中逐渐提高自己的自然性和流利度。可以利用某些shadowing site（影子练习网站）来获取资料。
- 录音与反馈：录下您的练习音频，并与原始演讲进行对比，及时纠正发音和语调，确保您在交流时更具感染力。
通过这些步骤，您将能够在英语口语练习中取得显著进步。记住，语言是情感的载体，真正的沟通需要用心去感受与表达。
什么是跟读法？
跟读法 (Shadowing) 是一种有科学依据的语言学习技巧，最初开发用于专业口译员的培训，并由多语言者Alexander Arguelles博士普及。这个方法简单而强大：您在听英语母语原声的同时立即大声重复——就像是一个延迟1-2秒紧跟说话者的影子。与被动听力或语法练习不同，跟读法强迫您的大脑和口腔肌肉同时处理并模仿真实的讲话模式。研究表明它能显着提高发音准确性，语调，节奏，连读，听力理解和口语流利度——使其成为雅思口语备考和真实英语交流最有效的方法之一。