Feel free to follow along with the transcript as you watch and listen to this episode!
Mary Daphne: Hello, advanced English learners. Welcome back to another listening comprehension slash native English speaker conversation. I'm joined by the one and only Greg. Thank you for joining me, Greg. Of course. So we do these so that you have practice with listening comprehension. You can test your comprehension skills.
Mary Daphne: You can work on your conversation skills, your communication skills, your prosody, your pronunciation, your vocab acquisition, and basically everything you need to be able to listen and speak in English. And read for that matter. All right, so today's topic is about this new technology that is emerging, which is voice detecting technology, and we're going to get more into it after that.
Mary Daphne: So let's get into it.
Mary Daphne: All right, so we're talking about this special type of voice AI technology. It's, there's really no specific way to talk about this yet, but I think we'll start, it'll start to unfold. So it's this AI powered technology that can help detect different types of mental problems or illness or anxiety or cardiovascular.
Mary Daphne: Issues, anything that is going awry in the body. And practitioners like doctors and medical practitioners and nurses are going to be leveraging the power of AI to help detect these things.
Greg: That's fascinating. So let me make sure that I've got the concept down. Yeah. Essentially what you're saying is there is a piece of software
Mary Daphne: Yes,
Greg: that can listen to someone's voice, to someone's speech, and based on the way that they're seeing things and perhaps the words, perhaps the words that they're using. And their choice of vocabulary, right? And maybe how loudly or softly they're speaking with all the different sort of nuances that goes into how someone says something and what they say.
Greg: It's able to make conclusions about the state of mind of that person. Is that conceptually the case here?
Mary Daphne: Conceptually? Yes. However, I think ultimately it will get to that point Greg, but right now what the articles that I'm reading are saying is that it's actually analyzing strictly your tone of voice, your prosody, which is , the stress patterns in the way you speak, the rising and falling, intonation, and other voice-based metrics.
Mary Daphne: Not looking at word choice. Words you're using expressions. So it's really just the voice.
Greg: In some ways that's the more subtle aspect of communication.
Mary Daphne: yeah.
Greg: It's not the words that you're using, but it's how you're saying them that reveals the most information.
Mary Daphne: Absolutely.
Greg: So it makes a lot of sense that's what they would focus on. And frankly, they may never need to focus on the vocabulary because the words that we choose to say doesn't necessarily represent the way we feel.
Mary Daphne: And it's also easier to pretend with words. I think like people can say, for example, if someone says, Ask me how I am, right?
Greg: How are you doing?
Mary Daphne: I'm alright. If I say that, I'm all right. That's all tone of voice. It's all Eh, I'm all right. Okay. There's the eh there. That makes you pause. Whereas if I say I'm all right, I might say it like that in an enthusiastic way, but also be feeling like, eh, I'm okay.
Greg: Yeah, That's a really good point.
Mary Daphne: Yeah.
Greg: One can always of course, disguise the way they feel, even, separate of word choice. Putting on a peppier to tone of voice,
Mary Daphne: Sure
Greg: but I get your point. In general, word choice has more to do with, the way that you're brought up your education, the amount that you read and your familiarity with the language, whereas the way you say something transcends all of that.
Mary Daphne: Yeah,
Greg: it also even transcends what language you're speaking. So I wouldn't be surprised if this software can detect whether you are happy or sad, anxious or calm, independent of which language you're speaking, , because it's really just listening to how you're saying it. And a lot is revealed by that.
Mary Daphne: So it's funny because it takes out of the equation, the emojis that they have in the doctor's office, which is like the smiley face, the on the spectrum of how do you feel or what's your pain level? And you're supposed to point to a number. I don't know if they really do that anymore, but it's on every pain metric, doctor's office wall, everything.
Mary Daphne: So that kind of takes that out of the equation. That's going to be a moot point at this point. If we have this kind of technology that is transcending the words and the, Oh, tell me how you feel. It's no, talk to me. And our AI robots, our machine learning will tell us how you really feel.
Greg: Totally. Yeah. And it brings up an interesting question.
Greg: And this is a debate that comes up, which is this then going to replace the doctor? Is this going to replace the clinician, if the software can do this?
Mary Daphne: Yeah.
Greg: And of course my answer is no.
Mary Daphne: No.
Greg: Not in any, foreseeable future. You still need the interpretation.
Greg: You need a doctor. Then say, Okay, this is what the machine, this is what the software is saying. Here's how I interpret this.
Mary Daphne: Yeah. And we need that human connection. I don't think many of us are prepared to completely erase that human connection from our lives, particularly when we're in a vulnerable position.
Mary Daphne: Like going to the doctor's office, even when you're going for a checkup. That can be a very much anxiety- inducing type of event where they're checking your blood pressure, they're checking this and that. Even if you're completely healthy and everything, you feel those butterflies in your stomach and you get a little anxious, which is understandable.
Greg: That's interesting you say that because I've heard the opposite.
Mary Daphne: Oh, have you?
Mary Daphne: Okay.
Greg: Which is that people are more likely to. if there isn't another human involved. Ah, so they're afraid if they go in and talk to an actual human, they're afraid of being judged.
Mary Daphne: Okay.
Greg: They're afraid of the psychiatrist or the therapist, thinking, even if the therapist isn't saying it, they're afraid that the therapist, thinks that they're weird. Or strange whatever when you're talking to a computer . Into a software.. The software, you know that it's not judging you because it's just a program and therefore they're more likely to open up and speak honestly.
Mary Daphne: But it is judging you. It's taking all the notes that it needs to. and then while somebody is going to interpret that and then judge you from there, I understand what you're saying in terms of the evaluation apprehension that people have. That's like stage fright, for example. Anytime we feel evaluated, like your teacher's evaluating you, you'll feel that, butterfly in your stomach sensation.
Mary Daphne: But that's an interesting point.
Greg: You said it though, the word evaluation versus judgment, right? Yeah. So the software is evaluating. A human may be judging you. So that's the difference, right?
Mary Daphne: There is a term, an evaluation, apprehension, which is that judgment. That's when teachers give you feedback and for example, let's say you're giving a speech and you see the teacher there, like writing notes, and then your attention goes just on that, the teacher giving notes.
Mary Daphne: As opposed to you giving your speech to your group of classmates or the audience or the meeting or whatever. . That's evaluation apprehension, but I don't know. There's something about a warm, friendly doctor being kind and empathetic. That makes me feel like that's an important thing to keep.
Mary Daphne: I don't know how many doctors are really like that.
Greg: I was going to say, I'm not sure you're pretty lucky if that's your doctor. The most doctors I've interacted with tend to be yeah, cold and distant just because they're so busy, right? They have so many clients to take care of. They just don't have time to be personal the way a computer could because a computer thing about this, Yeah.
Greg: A computer can immediately, right before you're, your meeting starts. It even simultaneously in parallel with meeting you. It knows all of your records right off the bat. It's not going to forget anything. Yeah. It knows everything about you. And it's going to interact with you in a very informed way.
Mary Daphne: How about this? The robot will have a nice happy tone, kind showing some empathy in the way that humans can read it.
Mary Daphne: then I would be okay with that, I think.
Greg: So , this is very much an end game, though. I don't even know it's the end game, but it's very much in the future.
Greg: . In the current state of affairs, I think we can both agree that this kind of software is certainly not going to replace an actual human doctor. It's really there just to enhance their ability to help the person.
Mary Daphne: And the thing that I'm wondering about I can understand the anxiety aspect maybe the depression aspect with picking it up from the tone of voice.
Mary Daphne: Again, this is AI powered technology, so a human is not doing this. The robot is . I'm wondering, they're saying that it can also pick up cardiovascular disease or issues. How can someone's tone of voice convey what their heart is doing.
Mary Daphne: Do you have any ideas?
Greg: I have thoughts.
Mary Daphne: Okay.
Greg: What I can say is think about how incredible it is that a watch we're wearing smart watches and smart rings right now.
Greg: Yeah. Think about how amazing those are. They just shine a little bit of light through your skin, into your blood vessels.
Mary Daphne: Yeah.
Greg: And based on how the blood vessels are, basically, how their light is reflected back into the watch. It can determine all kinds of things like your pulse, right? Blood, oxygen, you're, Yeah.
Greg: All of these very specific metrics just from the way that the light is essentially refracted in the blood vessels. So if we can do that with watches, it doesn't surprise me on a sort of technical level that we can determine elements of cardiovascular distress, Huh? Through the way that we talk.
Greg: Maybe it's the way we breathe. A respiratory rate. Yeah, that's what I was going to it could be anything. I'm sure there, there are all kinds of little secret clues that we give out that we don't even know we're giving out, that a machine can be trained to detect. And evaluate.
Mary Daphne: Yeah, so I think this is all really promising in the field of medicine and science because it'll help push, our learnings forward and ultimately reap better outcomes from such technology.
Mary Daphne: Maybe. Having better health spans, longer lives, better longevity. , which is I think, the goal for a lot of people.
Greg: Totally , also I always like taking human error out of it. So to the extent that we can remove some of the human biases that therapists might have. What if they were tired that morning and just weren't really on top of their game, so they weren't paying attention. A machine's always at the top of its game. And so it just, it really enhances the human elements of any kind of therapy or treatment.
Mary Daphne: A hundred percent. Do you think this is something that you would participate in if your doctor's office said hi, would you like to participate in this kind of study? Or would you like to test this out? Would you, what would you say? I feel like I would opt in
Greg: a hundred percent.
Mary Daphne: Because I think it'd be cool.
Greg: I just love it. I love the more that we can leverage technology to enhance our lives count me in .
Mary Daphne: Same. I'm with you, Greg.
Mary Daphne: What about you though? What do you think? Do you think technology is a barrier or is it. An enhancement
Mary Daphne: is it a facilitator or a barrier? What do you think? Would you use this type of technology? Let us know your thoughts. Also be sure to test your listening comprehension
Greg: speaking of evaluations.
Mary Daphne: Yes, exactly. And try out, the listening comprehension worksheets. You can get them on our website on advancedenglish.co. And you get them through the newsletter. So definitely sign up for those and then the next week you'll get the answers to the previous weeks what worksheet. So I would really recommend you doing that because it's a great way of, Milking more out of these conversations, so to speak.
Greg: A hundred percent.
Mary Daphne: All right we'll see you in the next one. Bye for now. Thanks for joining us.
Here are the answers to the listening comprehension questions: