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. And algorithms are deciding by sizing up the human voice.
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.
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Jobaline has taken that research and fed it into algorithms that interpret how a voice makes others feel and 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.
Through machine learning and multiple feedback loops, it keeps answering and homing in on Salazar's question: "What is the emotion that that voice is going to generate on the listener?"
SUBMIT YOUR VOICE
Do you have a voice for radio? NPR wants to hear it. We're collecting samples from listeners. We'll choose the best voice — based on a secret equation — and put it on air!
HOW TO SUBMIT:
1.) Go into a quiet room and launch a voice memo app on your smartphone.
2.) Hold the phone 1 foot away from your mouth, begin a recording and read this sentence: "I'm **FULL NAME** and this week on All Tech Considered, The Voice, public radio style, judged by computers." (Insert your real name.)
3.) Stop recording.
4.) Name the file with your FULL NAME.
5.) Email the file to nprcrowdsource@npr.org, subject line: Voice Submission. In the email, include your full name (it should match the file name) and the best number to reach you.
If we choose your voice, you'll get a call from NPR tech reporter Aarti Shahani.
THE FINE PRINT:
NPR will select several submissions to be sent by NPR to Jobaline, a company that evaluates voices for jobs. Your name will be used in the submission, but no other personally identifiable information will be given to Jobaline. By submitting your voice, you give NPR permission to submit your sample to Jobaline along with your name. You agree that NPR is not responsible for any actions of Jobaline or Jobaline's use of the submission.
Aside from the permissions granted in Paragraph 1, your submission to NPR is governed by our Terms of Use and Privacy Policy.
You grant NPR the right to use your recording for any purpose and in any and all media in perpetuity, and you waive any claims to privacy, publicity or related claims with respect to NPR's use of your submission.
You agree that, if selected in NPR's discretion, your voice may be used on air.
So far, Salazar says, the Jobaline secret formula can pinpoint if a voice is engaging, calming, and/or trustworthy.
Note: It's not a lie detector test. You could be a big liar, but just sound like someone honest.
Use It For Hiring
Big companies pay Jobaline to help them sift through thousands of applications to find the right workers for their hourly jobs. Human recruiters make the final judgment, but the startup determines the small pool that gets human consideration.
Jobaline says it has processed over half a million voices for positions including sales, janitorial staff and call center workers.
"In the hospitality industry, in the retail industry, you want people engaged. The average span of attention is four seconds," Salazar says.
That's very short.
The benefit of computer automation isn't just efficiency or cutting costs. Humans evaluating job candidates can get tired by the time applicant No. 25 comes through the door. Those doing the hiring can discriminate. But algorithms have stamina, and they do not factor in things like age, race, gender or sexual orientation. "That's the beauty of math," Salazar says. "It's blind."
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As a woman who has built a career on talking, I'm curious what the algorithms have to say about me.
My friends say I've got two voices: the inviting, empathetic "Hey how you doing, come on over" voice. And the "Don't mess with me. I'm getting work done" voice.
Salazar ventures to guess the intrinsic quality: "I'll say it's engaging and trustworthy. I don't think it will make the bar for calming. We'll see."
The algorithms agree. They say, with 95 percent certainty, that my voice is engaging to three-quarters of Americans.
So, I'm a good fit for radio.
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