Using algorithms to dissect and analyze the candidate’s voice is the latest contribution from technology to the job recruitment business.
A computer is going to let you know whether this lady you are interviewing can soothe angry cable customers or whether she should be selling perfume.
Years and years of scientific studies and focus groups have dissected the human voice and categorized the key emotions of the person speaking.
The company 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.
“We’re not analyzing how the speaker feels,” says Luis Salazar, CEO of Jobaline.. “That’s irrelevant.”
So far, Salazar says, the Jobaline secret formula can pinpoint if a voice is engaging, calming, and/or trustworthy.
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 in the listener?”
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.
The benefit of computer automation is not restricted to 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.”