(Part of the biometric product marketing expert series)
A recent PYMNTS article entitled “AI Voices Are Now Indistinguishable From Humans, Experts Say” includes the following about voice deepfakes:
“A new PLoS One study found that artificial intelligence has reached a point where cloned voices are indistinguishable from genuine ones. In the experiment, participants were asked to tellhuman voices from AI-generated ones across 80 samples. Cloned voices were mistaken for real in 58% of cases, while human voices were correctly identified only 62% of the time.”
What the study didn’t measure
Since you already read the title of this post, you know that I’m concentrating on the word “participants.”
The PLoS One experiment used PEOPLE to try to distinguish real voices from deepfake ones.
And people aren’t all that accurate. Never have been.
Before you decide that people can’t detect fake voices…
…why not have an ALGORITHM give it a try?
What the study did measure
But to be fair, that wasn’t the goal of the PLoS One study, which specifically focused on human perception.
“Recently, an intriguing effect was reported in AI-generated faces, where such face images were perceived as more human than images of real humans – a “hyperrealism effect.” Here, we tested whether a “hyperrealism effect” also exists for AI-generated voices.”
For the record, the researchers did NOT discover a hyperrealism effect in AI-generated voices.
Do you offer a solution?
But if future deepfake voices sound realer than real, then we will REALLY need the algorithms to spot the fakes.
And if your company has a voice deepfake detection solution, I could have talked about it right now in this post.
Or on your website.
Or on your social media.
Where your prospects can see it…and purchase it.
And money in your pocket is realer than real.
Let’s talk. https://bredemarket.com/mark/
Bredemarket 
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