If you're trying out for a job in sales, the person who judges your pitch may not be a person — it could be a computer.
Job recruitment is the newest frontier in automated labor, where algorithms are choosing who's the right fit to sell fast food or handle angry cable customers, by sizing up the human candidates' voices.
Let's take a voice you know: Al Pacino. Think back to how he sounds in The Godfather, Devil's Advocate, Scarface or this recent interview on Charlie Rose.
The actor speaks with different accents, different emotions, different ages — and his range is stunning. But in every version, Pacino's voice has a biological, inescapable fact.
"His tone of voice generates engagement, emotional engagement with audiences," says Luis Salazar, CEO of Jobaline. "It doesn't matter if you're screaming or not. That voice is engaging for the average American."
Years and years of scientific studies and focus groups have dissected the human voice and categorized the key emotions of the person speaking.
Jobaline has taken that research and fed it into algorithms that interpret how a voice makes others feel and then cross-checks its judgment with real human listeners. It's a departure from other data science. With facial recognition, for example, algorithms sift through your smile, your brow, to decide your mood.
"We're not analyzing how the speaker feels," Salazar says. "That's irrelevant."
Regardless of whether you're happy, sad or cracking jokes, your voice has a hidden, complicated architecture with an intrinsic signature — much like a fingerprint. And through trial and error, the algorithms can get better at predicting how things like energy and fundamental frequency impact others — be they people watching a movie, or cancer patients calling a help line.
