The technology, developed by UCLA researchers, is a game-changer for deaf parents and any parent who wants to better understand their little one's cries.
For deaf parents like Delbert and Sanaz Whetter, identifying not only when a baby is crying but why can be challenging. When they're in another room, they use cameras and remote noise-monitors to help keep an eye on their two children (one of whom is an infant), but in some cases, that technology falls short. Now, a new app developed by UCLA researchers appears to be a real game-changer for the Whetters—not to mention any parent who wants to better understand why their little one is wailing.
Called ChatterBaby, the app "analyzes the different types of frequencies that are in the cry and the different patterns of sound and silence,” Ariana Anderson, PhD, assistant professor in residence at the UCLA Semel Institute who spearheaded the development of the app, explained in a UCLA release. “For example, if a cry has a long period of silence, it’s more likely that the baby is fussy. If there are constant, high-volume frequencies, it’s more likely the baby is in pain.”
As a mom of four and statistician, Anderson keyed into the variations of cries in her own children. And then she thought, what if she could teach a computer to learn the differences among those cries? Obviously, a tool like that would be extremely helpful for parents. She began by creating a database of more than 2,000 infant cries and then used machine learning to build the algorithms used in the app.
“Current technology will alert parents when there is a sound coming from a child, but it doesn’t distinguish what type of sound it is,” Anderson shared. “This categorizes the cries to tell parents whether the baby is hungry or fussy or, with more than 90 percent accuracy, can determine if a baby is crying because it’s in pain."
Information in the database could ultimately help steer experts and parents toward other patterns and associations related to infant development, like autism spectrum disorder. There's a clear link, as UCLA points out that research has shown that babies at risk for autism show abnormal cry patterns even before they are diagnosed.
To that end, Anderson and her team will soon use ChatterBaby for a new study on the relationship between cry patterns and autism risk in both hearing and deaf children. "This study is unique because it brings the lab to the participant instead of the participant to the lab," Anderson says. "It’s open to anyone willing to download the ChatterBaby app on their iPhone or Android devices, record five seconds of their baby’s cries, then upload it to the database."
In the meantime, the fact that families like the Whetters—not to mention new parents and mothers suffering from PPD—can use ChatterBaby to better identify their babies' needs is an exciting, heartening step forward in the union of technology and parenting.