• kibiz0r
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    6 months ago

    Interacting with people whose tone doesn’t match their words may induce anxiety as well.

    Have they actually proven this is a good idea, or is this a “so preoccupied with whether or not they could” scenario?

    • Admiral Patrick@dubvee.org
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      6 months ago

      Have they actually proven this is a good idea, or is this a “so preoccupied with whether or not they could” scenario?

      It’s businesses “throwing AI into stuff”, so I’m going to say it’s a safe bet it’s the latter.

  • Nath@aussie.zone
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    6 months ago

    The biggest problem I see with this is the scenario where calls are recorded. They’re recorded in case we hit a “he said, she said” scenario. If some issue were to be escalated as far as a courtroom, the value of the recording to the business is greatly diminished.

    Even if the words the call agent gets are 100% verbatim, a lawyer can easily argue that a significant percentage of the message is in tone of voice. If that’s lost and the agent misses a nuance of the customer’s intent, they’ll have a solid case against the business.

    • Sneezycat@sopuli.xyz
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      6 months ago

      I see no problem: they can record the original call and postprocess it with AI live for the operators. The recordings would be the original audio.

      • geissi@feddit.de
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        6 months ago

        Besides providing verbatim records of who said what, there is a second can of worms in forming any sort of binding agreement if the two sides of the agreement are having two different conversations.

        I think this is what the part about the missed nuance means.

  • Admiral Patrick@dubvee.org
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    6 months ago

    This is giving me Black Mirror vibes. Like when that lady’s consciousness got put into a teddy bear, and she only had two ways to express herself:

    • Monkey wants a hug
    • Monkey loves you
    • TachyonTele@lemm.ee
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      6 months ago

      Most of the time angry customers don’t even understand what they’re angry at. They’ll 180 in a heartbeat if the agent can identify the actual issue. I agree, this is unnecessary.

      • Banzai51
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        6 months ago

        Based on my experience working in a call center, I wouldn’t call it unnecessary. People are fucked up.

        • TachyonTele@lemm.ee
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          6 months ago

          It’s not an easy job, and it can absolutely be rough and frustrating. But knowing what your customer is saying is pretty important.

        • Nath@aussie.zone
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          6 months ago

          I did phones in a different century, so I don’t know whether this would fly today. But, my go-to for someone like this was “ok, I think I see the problem here. Shall we go ahead and fix it or do you need to do more yelling first?

          I can’t remember that line ever not shutting them down instantly. I never took it personally, whatever they had going on they were never angry at me personally.

          Then again, I do remember firing a couple of customers (“we don’t want your business any more etc”) after I later became a manager and people were abusive to staff. So you could be right, also.

          • TachyonTele@lemm.ee
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            6 months ago

            Haha while I love the line, that last part would quickly get you pulled into a talk with management.

      • Admiral Patrick@dubvee.org
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        6 months ago

        Yep, 100%.

        In college, I worked at a call center for one of the worst Banks of America (oops, meant banks in America 😉). Can confirm that, and I dealt with a LOT of angry customers.

  • Cybrpwca@beehaw.org
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    6 months ago

    I think I get what the article is saying, but all I can imagine is Siri calmly reading to me the vilest insults ever written.

    • eveninghere@beehaw.org
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      6 months ago

      If you have pre-trained model or a classical voice matching algorithm as the basis, few samples might suffice.

    • Kissaki@beehaw.org
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      6 months ago

      I don’t think it seems like too few samples for it to work.

      What they train for is rather specific. To identify anger and hostility characteristics, and adjust pitch and inflection.

      Dunno if you meant it like that when you said “training people’s voices”, but they’re not replicating voices or interpreting meaning.

      learned to recognize and modify the vocal characteristics associated with anger and hostility. When a customer speaks to a call center operator, the model processes the incoming audio and adjusts the pitch and inflection of the customer’s voice to make it sound calmer and less threatening.

  • jet@hackertalks.com
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    6 months ago

    If they’re going to do this, then customers can get support via text messaging right? They’re not going to have to call in to talk to a computer to have their voice turned into text for an agent right?

    This isn’t about asymmetrically wasting the time of the customer so they don’t call support at all, right?

  • blindsight@beehaw.org
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    6 months ago

    This seems like it might work really well. We’ve evolved to be social creatures, and internalizing the emotions of others is literally baked into our DNA (mirror neurons), so filtering out the emotional “noise” from customers seems, to me, like a brilliant way to improve the working conditions for call centre workers.

    It’s not like you can’t also tell the emotional tone of the caller based on the words they’re saying, and the call centre employees will know that voices are being changed.

    Also, I’m not so sure about reporting on anonymous Redditor comments as the basis for journalism. I know why it’s done, but I’d rather hear what a trained psychologist has to say about this, y’know?

  • bitwolf@lemmy.one
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    6 months ago

    Dang, swearing was one of my strategies to get the bot to forward me to a representative

  • Xirup@yiffit.net
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    6 months ago

    In my country, 99% of the time you contact technical support, a poorly made bot responds (actually it is a while loop) with ambiguous and pre-written answers, and the only way to talk to a human is directly by going to the place in question, so nothing to worry about that here.